[{"data":1,"prerenderedAt":129},["ShallowReactive",2],{"blogposts:en":3},[4,17,28,38,49,60,71,82,94,106,117],{"id":5,"brow":6,"cover_image":7,"date":8,"excerpt":9,"extension":10,"heading":11,"main_content":12,"meta":13,"slug":14,"stem":15,"tagline":9,"__hash__":16},"blogposts\u002Fblogposts\u002Fnew-commons-incubator-webinar-data-commons-to-support-indigenous-languages-and-cultures.json","Event","https:\u002F\u002Fcms.thegovlab.com\u002Fassets\u002F3bc8927c-1c08-4144-9272-bb03b9b9c517","2026-07-17",null,"json","New Commons Incubator Webinar: Data Commons to Support Indigenous Languages and Cultures","\u003Cp dir=\"ltr\">What approaches can we adopt to ensure Indigenous communities control data about their language and culture? How do data commons represent one promising approach to this issue?\u003C\u002Fp>\n\u003Cp dir=\"ltr\">On 6 August at 11:00 AM EST \u002F 5:00 PM CET, in advance of the International Day of World’s Indigenous Peoples, The GovLab, Microsoft, and UNESCO will be hosting a webinar conversation on these topics. \u003C\u002Fp>\n\u003Cp dir=\"ltr\">The conversation will serve as both an opportunity to learn about current efforts being pursued by leading experts in the field of Indigenous data and to better understand the \u003Ca href=\"https:\u002F\u002Fnewcommons.ai\u002F\">New Commons Incubator\u003C\u002Fa>—a capacity-building program that aims to help Indigenous-led teams develop their ideas for data commons projects into fundable proposals. \u003C\u002Fp>\n\u003Cp dir=\"ltr\">The discussion, facilitated by The GovLab’s Stefaan Verhulst, will include members of the New \u003Ca href=\"https:\u002F\u002Fnewcommons.ai\u002Findigenous-languages\">Commons Incubator’s Steering Committee\u003C\u002Fa>, a group of Indigenous experts selected to ensure the work of the Incubator is productive and complementary to existing Indigenous-led work. They include:\u003C\u002Fp>\n\u003Cul>\n\u003Cli dir=\"ltr\" aria-level=\"1\">\n\u003Cp dir=\"ltr\" role=\"presentation\">\u003Ca href=\"http:\u002F\u002Flinkedin.com\u002Fin\u002Fchantalkamgne\">Chantal Kamgne\u003C\u002Fa>, Managing Director of Localizzz and Head of Research of EngageAfricaNLP\u003C\u002Fp>\n\u003C\u002Fli>\n\u003Cli dir=\"ltr\" aria-level=\"1\">\n\u003Cp dir=\"ltr\" role=\"presentation\">\u003Ca href=\"https:\u002F\u002Fsnre.arizona.edu\u002Fperson\u002Fnkwi-flores\">WarīNkwī Flores\u003C\u002Fa>, Founder and Translational Consultant, Kinray Hub\u003C\u002Fp>\n\u003C\u002Fli>\n\u003Cli dir=\"ltr\" aria-level=\"1\">\n\u003Cp dir=\"ltr\" role=\"presentation\">\u003Ca href=\"https:\u002F\u002Fprofiles.waikato.ac.nz\u002Fmaui.hudson\">Maui Hudson\u003C\u002Fa>, Director, Te Kotahi Research Institute, Office of Deputy Vice-Chancellor Maori\u003C\u002Fp>\n\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Cp>It will be preceded by a set of opening remarks from UNESCO’s Director of the Division for Digital Inclusion, Policies and Transformation, Guilherme Canela de Souza Godoi.\u003C\u002Fp>\n\u003Cp dir=\"ltr\">Don’t miss this exciting conversation and a chance to learn from leaders from around the world about topics such as the CARE Principles, Indigenous data sovereignty, and social licenses. Registration can be found \u003Ca href=\"https:\u002F\u002Fus02web.zoom.us\u002Fwebinar\u002Fregister\u002FWN_QKWWrDuLQrShi4C5uJGIVA#\u002F\">here\u003C\u002Fa>.\u003C\u002Fp>\n\u003Cp dir=\"ltr\">Learn more about the New Commons Incubator \u003Ca href=\"https:\u002F\u002Fnewcommons.ai\u002F\">here\u003C\u002Fa>.\u003C\u002Fp>",{},"new-commons-incubator-webinar-data-commons-to-support-indigenous-languages-and-cultures","blogposts\u002Fnew-commons-incubator-webinar-data-commons-to-support-indigenous-languages-and-cultures","3yk2XsRLMOnWav3lOFsTPd-YULBnuIABtvBnlnrmFsE",{"id":18,"brow":19,"cover_image":20,"date":21,"excerpt":9,"extension":10,"heading":22,"main_content":23,"meta":24,"slug":25,"stem":26,"tagline":9,"__hash__":27},"blogposts\u002Fblogposts\u002Fwhat-our-repository-reveals-about-data-commons-in-the-ai-era.json","Blog","https:\u002F\u002Fcms.thegovlab.com\u002Fassets\u002Fdb3280ca-e3c3-4667-8b31-08575df08e78","2026-07-13","What Our Repository Reveals About Data Commons in the AI Era","\u003Cp id=\"docs-internal-guid-bffbb4fc-7fff-446e-a989-6916c8e4ac8f\" dir=\"ltr\" style=\"line-height: 1.38; margin-top: 12pt; margin-bottom: 12pt;\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Over the last several months, The Open Data Policy Lab conducted an in-depth review of how the data commons gathered within our \u003C\u002Fspan>\u003Ca style=\"text-decoration: none;\" href=\"https:\u002F\u002Fdocs.google.com\u002Fspreadsheets\u002Fd\u002F1GPzU4Pspi-XOmJU13LvOUUPxtfTuRXcZMBw7lxkQRyY\u002Fedit?gid=0#gid=0\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #1155cc; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: underline; -webkit-text-decoration-skip: none; text-decoration-skip-ink: none; vertical-align: baseline; white-space: pre-wrap;\">Data Commons for Generative AI repository \u003C\u002Fspan>\u003C\u002Fa>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">align with the \u003C\u002Fspan>\u003Ca style=\"text-decoration: none;\" href=\"https:\u002F\u002Fopendatapolicylab.org\u002Farticles\u002Fdefining-data-commons\u002F\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #1155cc; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: underline; -webkit-text-decoration-skip: none; text-decoration-skip-ink: none; vertical-align: baseline; white-space: pre-wrap;\">six elements of our data commons assessment framework\u003C\u002Fspan>\u003C\u002Fa>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">: Public Purpose, Contributor Benefits, Funding and Support, Access Controls, Participatory Governance, and Accountability Mechanisms. \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp dir=\"ltr\" style=\"line-height: 1.38; margin-top: 12pt; margin-bottom: 12pt;\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">The review revealed both patterns and variation. Many initiatives articulate a public purpose, offer benefits to contributors, identify funding or support, and define access conditions. Participatory governance and accountability mechanisms varied more widely and often marked the clearest distinctions between data commons and adjacent models such as open data platforms, data cooperatives, and AI data pools.\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp dir=\"ltr\" style=\"line-height: 1.38; margin-top: 12pt; margin-bottom: 12pt;\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Our review highlighted that data commons take many institutional forms, including scientific research infrastructures, health data collaboratives, cultural and linguistic preservation efforts, industrial data spaces, and community-owned initiatives. Some operate globally or nationally, while others focus on specific sectors, communities, or local challenges.\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp dir=\"ltr\" style=\"line-height: 1.38; margin-top: 12pt; margin-bottom: 12pt;\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">In the sections that follow, we examine what the repository reveals through each element of our framework, offering a snapshot of how organizations across sectors are attempting to build, govern, and sustain shared data resources in an era shaped by data-intensive technologies and artificial intelligence.\u003C\u002Fspan>\u003C\u002Fp>\n\u003Ch1 dir=\"ltr\" style=\"line-height: 1.38; margin-top: 14pt; margin-bottom: 6pt;\">\u003Cspan style=\"font-size: 15pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Key Findings Across Our Six Elements of Data Commons \u003C\u002Fspan>\u003C\u002Fh1>\n\u003Ch2 dir=\"ltr\" style=\"line-height: 1.38; margin-top: 18pt; margin-bottom: 6pt;\">\u003Cspan style=\"font-size: 13.999999999999998pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Public Purpose\u003C\u002Fspan>\u003C\u002Fh2>\n\u003Cp dir=\"ltr\" style=\"line-height: 1.38; margin-top: 12pt; margin-bottom: 12pt;\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Public purpose generally refers to the commitment to transform data into a shared resource in the public’s interest. The initiatives in our repository formalized this commitment through missions, governance structures, or stewardship arrangements designed to align data use with broader societal goals. \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp dir=\"ltr\" style=\"line-height: 1.38; margin-top: 12pt; margin-bottom: 12pt;\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Several initiatives in our repository focus on scientific and clinical advancement. Initiatives such as \u003C\u002Fspan>\u003Ca style=\"text-decoration: none;\" href=\"https:\u002F\u002Fdata.midrc.org\u002F\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #1155cc; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: underline; -webkit-text-decoration-skip: none; text-decoration-skip-ink: none; vertical-align: baseline; white-space: pre-wrap;\">MIDRC\u003C\u002Fspan>\u003C\u002Fa>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">, the \u003C\u002Fspan>\u003Ca style=\"text-decoration: none;\" href=\"https:\u002F\u002Fdatacommons.cancer.gov\u002F\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #1155cc; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: underline; -webkit-text-decoration-skip: none; text-decoration-skip-ink: none; vertical-align: baseline; white-space: pre-wrap;\">NCI Cancer Research Data Commons\u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #1155cc; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: underline; -webkit-text-decoration-skip: none; text-decoration-skip-ink: none; vertical-align: baseline; white-space: pre-wrap;\">,\u003C\u002Fspan>\u003C\u002Fa>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"> \u003C\u002Fspan>\u003Ca style=\"text-decoration: none;\" href=\"https:\u002F\u002Fwww.insight.hdrhub.org\u002Fabout-insight\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #1155cc; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: underline; -webkit-text-decoration-skip: none; text-decoration-skip-ink: none; vertical-align: baseline; white-space: pre-wrap;\">INSIGHT\u003C\u002Fspan>\u003C\u002Fa>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">, and \u003C\u002Fspan>\u003Ca style=\"text-decoration: none;\" href=\"https:\u002F\u002Fdatahub.aida.scilifelab.se\u002Fabout\u002F\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #1155cc; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: underline; -webkit-text-decoration-skip: none; text-decoration-skip-ink: none; vertical-align: baseline; white-space: pre-wrap;\">AIDA Data Hub\u003C\u002Fspan>\u003C\u002Fa>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"> seek to improve disease detection, diagnosis, treatment, and care delivery by enabling researchers to access high-quality datasets that would otherwise remain siloed within individual hospitals, laboratories, or research institutions. In these cases, public purpose is closely tied to patient benefit, improved health outcomes, and the responsible reuse of sensitive biomedical data.\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp dir=\"ltr\" style=\"line-height: 1.38; margin-top: 12pt; margin-bottom: 12pt;\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Many initiatives identified seek to improve public-interest AI innovation, fairness, and inclusion. \u003C\u002Fspan>\u003Ca style=\"text-decoration: none;\" href=\"https:\u002F\u002Fmlcommons.org\u002Fdatasets\u002F\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #1155cc; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: underline; -webkit-text-decoration-skip: none; text-decoration-skip-ink: none; vertical-align: baseline; white-space: pre-wrap;\">MLCommons\u003C\u002Fspan>\u003C\u002Fa>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">, \u003C\u002Fspan>\u003Ca style=\"text-decoration: none;\" href=\"https:\u002F\u002Fcommonvoice.mozilla.org\u002Fen\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #1155cc; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: underline; -webkit-text-decoration-skip: none; text-decoration-skip-ink: none; vertical-align: baseline; white-space: pre-wrap;\">Common Voice\u003C\u002Fspan>\u003C\u002Fa>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">, \u003C\u002Fspan>\u003Ca style=\"text-decoration: none;\" href=\"https:\u002F\u002Fresearch.google\u002Fblog\u002Fwaxal-a-large-scale-open-resource-for-african-language-speech-technology\u002F\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #1155cc; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: underline; -webkit-text-decoration-skip: none; text-decoration-skip-ink: none; vertical-align: baseline; white-space: pre-wrap;\">WAXAL\u003C\u002Fspan>\u003C\u002Fa>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">, and the \u003C\u002Fspan>\u003Ca style=\"text-decoration: none;\" href=\"https:\u002F\u002Fwww.newcommons.ai\u002Fwinners\u002Fmalawi-voice-data-commons\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #1155cc; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: underline; -webkit-text-decoration-skip: none; text-decoration-skip-ink: none; vertical-align: baseline; white-space: pre-wrap;\">Malawi Voice Data Commons\u003C\u002Fspan>\u003C\u002Fa>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"> seek to expand access to representative, high-quality data so that AI development does not systematically exclude underrepresented languages, regions, or communities.\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp dir=\"ltr\" style=\"line-height: 1.38; margin-top: 12pt; margin-bottom: 12pt;\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Others \u003C\u002Fspan>\u003Ca style=\"text-decoration: none;\" href=\"http:\u002F\u002Fmedium.com\u002Fdata-stewards-network\u002F10-data-commons-for-cultural-knowledge-and-preservation-e0b4d3f33402\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #1155cc; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: underline; -webkit-text-decoration-skip: none; text-decoration-skip-ink: none; vertical-align: baseline; white-space: pre-wrap;\">aim to support\u003C\u002Fspan>\u003C\u002Fa>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"> cultural and linguistic preservation and revitalization. The \u003C\u002Fspan>\u003Ca style=\"text-decoration: none;\" href=\"https:\u002F\u002Fwww.ldaca.edu.au\u002F\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #1155cc; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: underline; -webkit-text-decoration-skip: none; text-decoration-skip-ink: none; vertical-align: baseline; white-space: pre-wrap;\">Language Data Commons of Australia\u003C\u002Fspan>\u003C\u002Fa>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">, \u003C\u002Fspan>\u003Ca style=\"text-decoration: none;\" href=\"https:\u002F\u002Fwww.clarin.eu\u002F\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #1155cc; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: underline; -webkit-text-decoration-skip: none; text-decoration-skip-ink: none; vertical-align: baseline; white-space: pre-wrap;\">CLARIN\u003C\u002Fspan>\u003C\u002Fa>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">, \u003C\u002Fspan>\u003Ca style=\"text-decoration: none;\" href=\"https:\u002F\u002Fopenheritage3d.org\u002Fabout\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #1155cc; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: underline; -webkit-text-decoration-skip: none; text-decoration-skip-ink: none; vertical-align: baseline; white-space: pre-wrap;\">Open Heritage\u003C\u002Fspan>\u003C\u002Fa>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">, \u003C\u002Fspan>\u003Ca style=\"text-decoration: none;\" href=\"https:\u002F\u002Fwww.kbr.be\u002Fen\u002Fprojects\u002Fmetabelgica\u002F\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #1155cc; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: underline; -webkit-text-decoration-skip: none; text-decoration-skip-ink: none; vertical-align: baseline; white-space: pre-wrap;\">MetaBelgica\u003C\u002Fspan>\u003C\u002Fa>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">, and the \u003C\u002Fspan>\u003Ca style=\"text-decoration: none;\" href=\"https:\u002F\u002Fwww.dataspace-culturalheritage.eu\u002Fen#about-the-data-space\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #1155cc; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: underline; -webkit-text-decoration-skip: none; text-decoration-skip-ink: none; vertical-align: baseline; white-space: pre-wrap;\">Common European Data Space for Cultural Heritage\u003C\u002Fspan>\u003C\u002Fa>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"> treat data as a vehicle for preserving cultural memory, linguistic diversity, and shared knowledge. These initiatives emphasize long-term stewardship, responsible access, cultural authority, and the preservation of resources that might otherwise disappear.\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp dir=\"ltr\" style=\"line-height: 1.38; margin-top: 12pt; margin-bottom: 12pt;\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">We also identified initiatives that pursue public purpose through democratic values, environmental resilience, and community self-determination. For example, the \u003C\u002Fspan>\u003Ca style=\"text-decoration: none;\" href=\"https:\u002F\u002Fpublicinterestcorpus.org\u002F\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #1155cc; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: underline; -webkit-text-decoration-skip: none; text-decoration-skip-ink: none; vertical-align: baseline; white-space: pre-wrap;\">Public Interest Corpus\u003C\u002Fspan>\u003C\u002Fa>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"> seeks to support public-interest AI research and a more informed knowledge ecosystem. \u003C\u002Fspan>\u003Ca style=\"text-decoration: none;\" href=\"https:\u002F\u002Fposmo.coop\u002F\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #1155cc; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: underline; -webkit-text-decoration-skip: none; text-decoration-skip-ink: none; vertical-align: baseline; white-space: pre-wrap;\">Posmo\u003C\u002Fspan>\u003C\u002Fa>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"> advances informational self-determination by giving mobility-data contributors greater control over how their data is used. \u003C\u002Fspan>\u003Ca style=\"text-decoration: none;\" href=\"http:\u002F\u002Fgainforest.earth\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #1155cc; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: underline; -webkit-text-decoration-skip: none; text-decoration-skip-ink: none; vertical-align: baseline; white-space: pre-wrap;\">GainForest.Earth\u003C\u002Fspan>\u003C\u002Fa>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"> supports local and Indigenous communities in collecting and governing biodiversity and environmental data. Sectoral commons such as \u003C\u002Fspan>\u003Ca style=\"text-decoration: none;\" href=\"https:\u002F\u002Fcatena-x.net\u002F\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #1155cc; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: underline; -webkit-text-decoration-skip: none; text-decoration-skip-ink: none; vertical-align: baseline; white-space: pre-wrap;\">Catena-X\u003C\u002Fspan>\u003C\u002Fa>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"> and the \u003C\u002Fspan>\u003Ca style=\"text-decoration: none;\" href=\"https:\u002F\u002Fmobility-dataspace.eu\u002F\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #1155cc; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: underline; -webkit-text-decoration-skip: none; text-decoration-skip-ink: none; vertical-align: baseline; white-space: pre-wrap;\">Mobility Data Space\u003C\u002Fspan>\u003C\u002Fa>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"> pursue public value through industry-wide coordination, sustainability, interoperability, and supply-chain transparency.\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp dir=\"ltr\" style=\"line-height: 1.38; margin-top: 12pt; margin-bottom: 12pt;\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">The repository shows that public purpose is not a single objective but a spectrum of social commitments. Some initiatives define the public in broad societal terms, while others focus on specific communities, sectors, or domains. \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp> \u003C\u002Fp>\n\u003Ch2 dir=\"ltr\" style=\"line-height: 1.38; margin-top: 18pt; margin-bottom: 6pt;\">\u003Cspan style=\"font-size: 13.999999999999998pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Contributor Benefits\u003C\u002Fspan>\u003C\u002Fh2>\n\u003Cp dir=\"ltr\" style=\"line-height: 1.38; margin-top: 12pt; margin-bottom: 12pt;\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Throughout the repository, contributors are treated as stakeholders whose continued participation depends on tangible value. Like public purpose, contributor benefits appear in nearly all initiatives in the repository. The few exceptions are typically initiatives in development, where benefits are anticipated but not yet fully operationalized.\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp dir=\"ltr\" style=\"line-height: 1.38; margin-top: 12pt; margin-bottom: 12pt;\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">The most prevalent contributor benefit is visibility and academic credit. Initiatives such as \u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">AIDA Data Hub\u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"> make datasets more FAIR and citable by \u003C\u002Fspan>\u003Ca style=\"text-decoration: none;\" href=\"https:\u002F\u002Fdatahub.aida.scilifelab.se\u002Fservices\u002Fdata-sharing\u002F\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #1155cc; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: underline; -webkit-text-decoration-skip: none; text-decoration-skip-ink: none; vertical-align: baseline; white-space: pre-wrap;\">assigning Digital Object Identifiers\u003C\u002Fspan>\u003C\u002Fa>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">, allowing researchers to receive formal recognition when their datasets are reused. The \u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Health Data Hub\u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"> similarly \u003C\u002Fspan>\u003Ca style=\"text-decoration: none;\" href=\"https:\u002F\u002Fwww.health-data-hub.fr\u002Fpage\u002Ffaq-english\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #1155cc; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: underline; -webkit-text-decoration-skip: none; text-decoration-skip-ink: none; vertical-align: baseline; white-space: pre-wrap;\">reinforces contributor visibility\u003C\u002Fspan>\u003C\u002Fa>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"> by requiring projects to cite source databases and by informing contributors when their data is reused.\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp dir=\"ltr\" style=\"line-height: 1.38; margin-top: 12pt; margin-bottom: 12pt;\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Several initiatives support their contributors through technical and operational support. Some initiatives reduce the burdens of data management by helping contributors with extraction, documentation, harmonization, secure access workflows, and infrastructure. The \u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Mobility Data Space\u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">, for example, provides a \u003C\u002Fspan>\u003Ca style=\"text-decoration: none;\" href=\"https:\u002F\u002Fmobility-dataspace.eu\u002Fdata-catalogue\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #1155cc; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: underline; -webkit-text-decoration-skip: none; text-decoration-skip-ink: none; vertical-align: baseline; white-space: pre-wrap;\">Connector-as-a-Service\u003C\u002Fspan>\u003C\u002Fa>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"> model that allows organizations to exchange data securely without maintaining complex technical infrastructure themselves. The \u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">HathiTrust Research Center\u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"> offers members \u003C\u002Fspan>\u003Ca style=\"text-decoration: none;\" href=\"https:\u002F\u002Fwww.hathitrust.org\u002Fmember-libraries\u002Fservices-programs\u002Fhtrc\u002F\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #1155cc; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: underline; -webkit-text-decoration-skip: none; text-decoration-skip-ink: none; vertical-align: baseline; white-space: pre-wrap;\">specialized developer support\u003C\u002Fspan>\u003C\u002Fa>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">, technical expertise, and high-capacity computing environments for large-scale text and data mining. \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp dir=\"ltr\" style=\"line-height: 1.38; margin-top: 12pt; margin-bottom: 12pt;\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Another benefit is influence over standards, strategy, and governance. \u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Catena-X\u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"> gives participating organizations opportunities to \u003C\u002Fspan>\u003Ca style=\"text-decoration: none;\" href=\"https:\u002F\u002Fcatena-x.academy\u002Fwp-content\u002Fuploads\u002F2024\u002F09\u002F8.1_CX-Association-History-Tasks-Goals.pdf\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #1155cc; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: underline; -webkit-text-decoration-skip: none; text-decoration-skip-ink: none; vertical-align: baseline; white-space: pre-wrap;\">co-create industry standards\u003C\u002Fspan>\u003C\u002Fa>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">, define API specifications, and shape certification requirements for the automotive ecosystem. In the \u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Posmo\u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"> cooperative, individuals who contribute mobility data gain membership rights and can participate directly in decisions about how the data is used and which institutions may access it. These models treat governance itself as a contributor benefit by giving participants influence over the future direction of the commons. \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp dir=\"ltr\" style=\"line-height: 1.38; margin-top: 12pt; margin-bottom: 12pt;\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Some initiatives provide financial incentives or data enrichment. \u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">AIDA Data Hub \u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">offers \u003C\u002Fspan>\u003Ca style=\"text-decoration: none;\" href=\"https:\u002F\u002Fdatahub.aida.scilifelab.se\u002Fservices\u002F\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #1155cc; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: underline; -webkit-text-decoration-skip: none; text-decoration-skip-ink: none; vertical-align: baseline; white-space: pre-wrap;\">discounts and other incentives\u003C\u002Fspan>\u003C\u002Fa>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"> for contributors of prioritized datasets while also supporting researchers to extract, enrich, and prepare data for broader sharing and reuse. \u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">GainForest.Earth \u003C\u002Fspan>\u003Ca style=\"text-decoration: none;\" href=\"https:\u002F\u002Fdocs.gainforest.earth\u002Fsolutions\u002Fconservation-data-income\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #1155cc; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: underline; -webkit-text-decoration-skip: none; text-decoration-skip-ink: none; vertical-align: baseline; white-space: pre-wrap;\">rewards communities\u003C\u002Fspan>\u003C\u002Fa>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"> for contributing biodiversity data through community-defined pricing models while also providing training, AI tools, and conservation technologies that strengthen local capacity to collect, steward, and benefit from environmental data. The \u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Health Data Hub\u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"> offers another type of benefit, linking and \u003C\u002Fspan>\u003Ca style=\"text-decoration: none;\" href=\"https:\u002F\u002Fwww.medizininformatik-initiative.de\u002Fsites\u002Fdefault\u002Ffiles\u002F2020-11\u002FPresentationHDHNov2020.pptx_0.pdf\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #1155cc; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: underline; -webkit-text-decoration-skip: none; text-decoration-skip-ink: none; vertical-align: baseline; white-space: pre-wrap;\">enriching contributed\u003C\u002Fspan>\u003C\u002Fa>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"> datasets with additional health data resources, allowing contributors to derive greater value from the data they originally supplied.\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp> \u003C\u002Fp>\n\u003Ch2 dir=\"ltr\" style=\"line-height: 1.38; margin-top: 18pt; margin-bottom: 6pt;\">\u003Cspan style=\"font-size: 13.999999999999998pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Funding and Support\u003C\u002Fspan>\u003C\u002Fh2>\n\u003Cp dir=\"ltr\" style=\"line-height: 1.38; margin-top: 12pt; margin-bottom: 12pt;\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Many initiatives within our repository begin with grants, public seed funding, or pilot support, but durable commons require longer-term arrangements to cover the ongoing costs of infrastructure, stewardship, governance, accountability, and community engagement. As we have \u003C\u002Fspan>\u003Ca style=\"text-decoration: none;\" href=\"https:\u002F\u002Fopendatapolicylab.org\u002Farticles\u002Fblog-post-emerging-funding-and-business-models-for-data-commons-a-comparison\u002F\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #1155cc; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: underline; -webkit-text-decoration-skip: none; text-decoration-skip-ink: none; vertical-align: baseline; white-space: pre-wrap;\">discussed elsewhere\u003C\u002Fspan>\u003C\u002Fa>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">, funding models frequently overlap and evolve over time.\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp dir=\"ltr\" style=\"line-height: 1.38; margin-top: 12pt; margin-bottom: 12pt;\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">The majority of initiatives are supported by multiple organizations through consortium or collaborative arrangements. \u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Catena-X\u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">, \u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">MLCommons\u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">, \u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">CLARIN\u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">, and \u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Open Heritage\u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"> bring together public agencies, research institutions, companies, philanthropies, and civil society organizations that contribute funding, infrastructure, technical expertise, governance labor, or domain knowledge. \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp dir=\"ltr\" style=\"line-height: 1.38; margin-top: 12pt; margin-bottom: 12pt;\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">A second major theme is public or government-backed funding. \u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Health Data Hub\u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">, \u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">INSIGHT\u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">, the \u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">NCI Cancer Research Data Commons\u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">, \u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Mobility Data Space\u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">, and the \u003C\u002Fspan>\u003Ca style=\"text-decoration: none;\" href=\"https:\u002F\u002Feosc.eu\u002Feosc-about\u002F\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #1155cc; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: underline; -webkit-text-decoration-skip: none; text-decoration-skip-ink: none; vertical-align: baseline; white-space: pre-wrap;\">European Open Science Cloud\u003C\u002Fspan>\u003C\u002Fa>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"> depend on funding from government agencies, research councils, public institutions, or state-supported programs. \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp dir=\"ltr\" style=\"line-height: 1.38; margin-top: 12pt; margin-bottom: 12pt;\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Other initiatives sustain themselves through membership dues, service models, or donations. \u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">HathiTrust\u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">, \u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">AIDA Data Hub\u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">, \u003C\u002Fspan>\u003Ca style=\"text-decoration: none;\" href=\"https:\u002F\u002Fosmfoundation.org\u002F\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #1155cc; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: underline; -webkit-text-decoration-skip: none; text-decoration-skip-ink: none; vertical-align: baseline; white-space: pre-wrap;\">OpenStreetMap\u003C\u002Fspan>\u003C\u002Fa>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">, and parts of the \u003C\u002Fspan>\u003Ca style=\"text-decoration: none;\" href=\"https:\u002F\u002Fwww.wikidata.org\u002Fwiki\u002FWikidata:Main_Page\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #1155cc; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: underline; -webkit-text-decoration-skip: none; text-decoration-skip-ink: none; vertical-align: baseline; white-space: pre-wrap;\">Wikimedia\u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #1155cc; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: underline; -webkit-text-decoration-skip: none; text-decoration-skip-ink: none; vertical-align: baseline; white-space: pre-wrap;\"> \u003C\u002Fspan>\u003C\u002Fa>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">ecosystem rely on combinations of institutional memberships, service fees, philanthropic donations, and volunteer contributions. Initiatives such as \u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Common Voice\u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">, the \u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Public Interest Corpus\u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">, \u003C\u002Fspan>\u003Ca style=\"text-decoration: none;\" href=\"https:\u002F\u002Ftransfer.art\u002Ftrust\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #1155cc; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: underline; -webkit-text-decoration-skip: none; text-decoration-skip-ink: none; vertical-align: baseline; white-space: pre-wrap;\">TRANSFER Data Trust\u003C\u002Fspan>\u003C\u002Fa>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">, \u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">GainForest.Earth\u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">, and the \u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Malawi Voice Data Commons\u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"> rely on philanthropic, grant-based, or early-stage development funding. These initiatives depend on grants, fiscal sponsorship, foundation support, or pilot funding to address public-interest challenges such as democratizing AI, strengthening community data governance, preserving language and cultural resources, or expanding access to scientific and educational data.\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp> \u003C\u002Fp>\n\u003Ch2 dir=\"ltr\" style=\"line-height: 1.38; margin-top: 18pt; margin-bottom: 6pt;\">\u003Cspan style=\"font-size: 13.999999999999998pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Access Controls\u003C\u002Fspan>\u003C\u002Fh2>\n\u003Cp dir=\"ltr\" style=\"line-height: 1.38; margin-top: 12pt; margin-bottom: 12pt;\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Across the repository, access is rarely treated as simply “open” or “closed.” Instead, initiatives use legal, procedural, technical, and community-based mechanisms to balance data availability with privacy, consent, intellectual property, cultural authority, commercial sensitivity, and data sovereignty. \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp dir=\"ltr\" style=\"line-height: 1.38; margin-top: 12pt; margin-bottom: 12pt;\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Several initiatives use ethical review processes to determine whether data access should be granted. \u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">INSIGHT\u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">, for example, uses the Five Safes framework and routes feasible applications to its \u003C\u002Fspan>\u003Ca style=\"text-decoration: none;\" href=\"https:\u002F\u002Fwww.insight.hdrhub.org\u002Fdata-trust-advisory-board\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #1155cc; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: underline; -webkit-text-decoration-skip: none; text-decoration-skip-ink: none; vertical-align: baseline; white-space: pre-wrap;\">Data Trust Advisory Board\u003C\u002Fspan>\u003C\u002Fa>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">, which includes patient and public stakeholders and evaluates whether proposed uses balance scientific discovery with public benefit. The \u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Health Data Hub\u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"> follows a similarly formal process, \u003C\u002Fspan>\u003Ca style=\"text-decoration: none;\" href=\"https:\u002F\u002Fwww.health-data-hub.fr\u002Fstarter-kit\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #1155cc; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: underline; -webkit-text-decoration-skip: none; text-decoration-skip-ink: none; vertical-align: baseline; white-space: pre-wrap;\">requiring\u003C\u002Fspan>\u003C\u002Fa>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"> scientific and ethical review before authorization by France’s national data protection authority.\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp dir=\"ltr\" style=\"line-height: 1.38; margin-top: 12pt; margin-bottom: 12pt;\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">A second model is secure analysis, where users work with data inside a controlled environment. The \u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">HathiTrust Research Center\u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"> uses \u003C\u002Fspan>\u003Ca style=\"text-decoration: none;\" href=\"https:\u002F\u002Fwww.hathitrust.org\u002Fthe-collection\u002Fterms-conditions\u002Fnon-consumptive-use-policy\u002F\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #1155cc; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: underline; -webkit-text-decoration-skip: none; text-decoration-skip-ink: none; vertical-align: baseline; white-space: pre-wrap;\">Data Capsules\u003C\u002Fspan>\u003C\u002Fa>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"> to support computational research on protected collections while preventing substantial portions of raw texts from leaving the system; exports must be reviewed to ensure they do not reproduce protected expressive content. \u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">INSIGHT\u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"> similarly provides access through a \u003C\u002Fspan>\u003Ca style=\"text-decoration: none;\" href=\"https:\u002F\u002Fwww.insight.hdrhub.org\u002Fsecure-research-environment\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #1155cc; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: underline; -webkit-text-decoration-skip: none; text-decoration-skip-ink: none; vertical-align: baseline; white-space: pre-wrap;\">Secure Research Environment\u003C\u002Fspan>\u003C\u002Fa>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">, where researchers work in controlled virtual environments and outputs are reviewed before export. \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp dir=\"ltr\" style=\"line-height: 1.38; margin-top: 12pt; margin-bottom: 12pt;\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Other initiatives rely on credentials, training, and data use agreements to ensure that only qualified or accountable users gain access. \u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">MIDRC\u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">, for example, requires \u003C\u002Fspan>\u003Ca style=\"text-decoration: none;\" href=\"https:\u002F\u002Fwww.midrc.org\u002Fuser-registration\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #1155cc; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: underline; -webkit-text-decoration-skip: none; text-decoration-skip-ink: none; vertical-align: baseline; white-space: pre-wrap;\">user registration\u003C\u002Fspan>\u003C\u002Fa>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">, institutional authentication, and agreement to detailed data use conditions governing redistribution, re-identification, publication, and commercial use. \u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Health Data Nexus\u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"> similarly combines institutional authorization, mandatory ethics training, and \u003C\u002Fspan>\u003Ca style=\"text-decoration: none;\" href=\"https:\u002F\u002Fhealthdatanexus.ai\u002Fabout\u002Fstart\u002F\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #1155cc; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: underline; -webkit-text-decoration-skip: none; text-decoration-skip-ink: none; vertical-align: baseline; white-space: pre-wrap;\">data use agreements \u003C\u002Fspan>\u003C\u002Fa>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">before granting access to specific datasets. \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp dir=\"ltr\" style=\"line-height: 1.38; margin-top: 12pt; margin-bottom: 12pt;\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">For lower-risk or more openly shared resources, access controls often take the form of standardized licenses, APIs, and tiered access categories. \u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">CLARIN\u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"> organizes language resources into public, academic, and restricted-\u003C\u002Fspan>\u003Ca style=\"text-decoration: none;\" href=\"https:\u002F\u002Fwww.clarin.eu\u002Fcontent\u002Flicenses-and-clarin-categories\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #1155cc; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: underline; -webkit-text-decoration-skip: none; text-decoration-skip-ink: none; vertical-align: baseline; white-space: pre-wrap;\">access categories\u003C\u002Fspan>\u003C\u002Fa>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">, while initiatives such as \u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Common Voice\u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"> and \u003C\u002Fspan>\u003Ca style=\"text-decoration: none;\" href=\"https:\u002F\u002Fwww.institutionaldatainitiative.org\u002Finstitutional-books\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #1155cc; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: underline; -webkit-text-decoration-skip: none; text-decoration-skip-ink: none; vertical-align: baseline; white-space: pre-wrap;\">Institutional Books 1.0\u003C\u002Fspan>\u003C\u002Fa>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"> rely on open licenses, attribution requirements, platform terms, or API-based access. These models maximize reuse while still establishing expectations for lawful and responsible use.\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp dir=\"ltr\" style=\"line-height: 1.38; margin-top: 12pt; margin-bottom: 12pt;\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Industrial and federated data spaces use access controls rooted in data sovereignty. \u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Mobility Data Space\u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"> and \u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Catena-X\u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"> allow data to remain with providers while exchange is mediated through connectors, contracts, and shared technical standards. \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp> \u003C\u002Fp>\n\u003Ch2 dir=\"ltr\" style=\"line-height: 1.38; margin-top: 18pt; margin-bottom: 6pt;\">\u003Cspan style=\"font-size: 13.999999999999998pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Participatory Governance\u003C\u002Fspan>\u003C\u002Fh2>\n\u003Cp dir=\"ltr\" style=\"line-height: 1.38; margin-top: 12pt; margin-bottom: 12pt;\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Participatory governance is the primary feature that distinguishes a data commons from a platform for data access. Throughout the repository, many initiatives involved consultation, contribution, or co-design, but only some gave participants authority over access conditions, technical standards, strategic priorities, or future development. In some commons, individuals or communities participate directly; in others, participation occurs through organizations, institutions, or sectoral representatives. What matters is not who participates, but whether decision-making authority is meaningfully shared.\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp dir=\"ltr\" style=\"line-height: 1.38; margin-top: 12pt; margin-bottom: 12pt;\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">One governance model is independent stakeholder oversight, where affected groups or public representatives help determine whether data use is legitimate. \u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">INSIGHT \u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">gives its Data Trust Advisory Board authority over the assessment criteria used to approve or deny data access requests. The \u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Health Data Hub\u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"> follows a more institutional version of this model through \u003C\u002Fspan>\u003Ca style=\"text-decoration: none;\" href=\"https:\u002F\u002Fwww.health-data-hub.fr\u002Fcesrees\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #1155cc; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: underline; -webkit-text-decoration-skip: none; text-decoration-skip-ink: none; vertical-align: baseline; white-space: pre-wrap;\">CESREES\u003C\u002Fspan>\u003C\u002Fa>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">—the Ethical and Scientific Committee for Research, Studies and Evaluations in the field of Health—which evaluates the scientific relevance, ethical character, and public-interest value of proposed projects.\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp dir=\"ltr\" style=\"line-height: 1.38; margin-top: 12pt; margin-bottom: 12pt;\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">A second model is collaborative standard-setting, where participating organizations collectively shape the technical and operational rules of the commons. This approach is common in consortium-based initiatives where membership is held by institutions. In \u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Catena-X\u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">, for example, members participate in topic-specific \u003C\u002Fspan>\u003Ca style=\"text-decoration: none;\" href=\"https:\u002F\u002Fcatena-x.net\u002Fwp-content\u002Fuploads\u002F2025\u002F03\u002FCatena-X_Organization_Chart.pdf\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #1155cc; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: underline; -webkit-text-decoration-skip: none; text-decoration-skip-ink: none; vertical-align: baseline; white-space: pre-wrap;\">working groups\u003C\u002Fspan>\u003C\u002Fa>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"> that define standards, data models, API specifications, and software priorities for the automotive ecosystem. \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp dir=\"ltr\" style=\"line-height: 1.38; margin-top: 12pt; margin-bottom: 12pt;\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">A third model centers on community sovereignty and member control. \u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Posmo\u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"> gives every individual who contributes data the right to become a member and participate in decisions about which institutions may access aggregated datasets. \u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">TRANSFER Data Trust\u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"> similarly uses a \u003C\u002Fspan>\u003Ca style=\"text-decoration: none;\" href=\"https:\u002F\u002Ftransfer.art\u002Ftrust\u002Fgovernance#:~:text=TRANSFER%20Data%20Trust%20is%20a,supporters%20informed%20of%20our%20progress.\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #1155cc; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: underline; -webkit-text-decoration-skip: none; text-decoration-skip-ink: none; vertical-align: baseline; white-space: pre-wrap;\">member-owned cooperative model\u003C\u002Fspan>\u003C\u002Fa>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"> that gives artists and cultural organizations a direct role in shaping stewardship and governance. The \u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Language Data Commons of Australia\u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"> extends this logic to Indigenous and community authority by using governance structures informed by \u003C\u002Fspan>\u003Ca style=\"text-decoration: none;\" href=\"https:\u002F\u002Fwww.ldaca.edu.au\u002Fabout\u002Fprinciples\u002F\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #1155cc; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: underline; -webkit-text-decoration-skip: none; text-decoration-skip-ink: none; vertical-align: baseline; white-space: pre-wrap;\">CARE principles\u003C\u002Fspan>\u003C\u002Fa>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"> to support appropriate control over sensitive linguistic collections.\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp dir=\"ltr\" style=\"line-height: 1.38; margin-top: 12pt; margin-bottom: 12pt;\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Other initiatives rely on strategic steering and advisory bodies to guide priorities. \u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Artsdata\u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">, for example, is governed by the \u003C\u002Fspan>\u003Ca style=\"text-decoration: none;\" href=\"https:\u002F\u002Fkg.artsdata.ca\u002F\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #1155cc; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: underline; -webkit-text-decoration-skip: none; text-decoration-skip-ink: none; vertical-align: baseline; white-space: pre-wrap;\">Artsdata Community Group\u003C\u002Fspan>\u003C\u002Fa>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">, which brings together data providers, users, financial supporters, and sector experts to guide the governance and evolution of the shared knowledge graph.\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp dir=\"ltr\" style=\"line-height: 1.38; margin-top: 12pt; margin-bottom: 12pt;\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Like the other elements, participatory governance does not take a single institutional form. It can involve patient and public oversight, collaborative ecosystem governance, cooperative ownership, Indigenous and community data sovereignty, advisory councils, or technical standard-setting. It may operate through individual contributors, community representatives, or participating organizations. What distinguishes a data commons is the distribution of authority: meaningful decisions about access, stewardship, standards, and future development are shared rather than retained exclusively by a central actor.\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp> \u003C\u002Fp>\n\u003Ch2 dir=\"ltr\" style=\"line-height: 1.38; margin-top: 18pt; margin-bottom: 6pt;\">\u003Cspan style=\"font-size: 13.999999999999998pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Accountability Mechanisms\u003C\u002Fspan>\u003C\u002Fh2>\n\u003Cp dir=\"ltr\" style=\"line-height: 1.38; margin-top: 12pt; margin-bottom: 12pt;\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Accountability mechanisms clarify who is responsible for data use, how compliance is monitored, and how contributors, communities, or the public can assess whether the commons is being used appropriately.\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp dir=\"ltr\" style=\"line-height: 1.38; margin-top: 12pt; margin-bottom: 12pt;\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Several initiatives use public transparency and usage reporting. \u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">INSIGHT’s\u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"> \u003C\u002Fspan>\u003Ca style=\"text-decoration: none;\" href=\"https:\u002F\u002Fwww.insight.hdrhub.org\u002Fdata-use-register\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #1155cc; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: underline; -webkit-text-decoration-skip: none; text-decoration-skip-ink: none; vertical-align: baseline; white-space: pre-wrap;\">Data Use Register\u003C\u002Fspan>\u003C\u002Fa>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"> provides an accessible record of the project title, lead applicant, and purpose for each study granted access to NHS patient data. The \u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Health Data Hub\u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"> similarly publishes information about datasets in its catalogue and the research projects using them. The \u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Public Interest Corpus\u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"> also emphasizes \u003C\u002Fspan>\u003Ca style=\"text-decoration: none;\" href=\"https:\u002F\u002Fpublicinterestcorpus.org\u002Fprinciples-and-goals\u002F#:~:text=Data%20Nutrition%20Label.-,The%20Public%20Interest%20Corpus%20%E2%80%A6,makes%20use%20of%20the%20corpus.\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #1155cc; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: underline; -webkit-text-decoration-skip: none; text-decoration-skip-ink: none; vertical-align: baseline; white-space: pre-wrap;\">transparency \u003C\u002Fspan>\u003C\u002Fa>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">around corpus composition and future modifications as a way to build trust in downstream research.\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp dir=\"ltr\" style=\"line-height: 1.38; margin-top: 12pt; margin-bottom: 12pt;\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">A second model is institutional and professional responsibility. \u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">AIDA Data Hub\u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"> requires access requests to be led by a qualified researcher affiliated with a responsible research institution, which remains accountable for safeguarding the data according to its policies and applicable law. At the \u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Health Data Nexus\u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">, users must sign a Data Use Agreement for each dataset they wish to access, linking their institutional identity to specific ethical and legal obligations.\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp dir=\"ltr\" style=\"line-height: 1.38; margin-top: 12pt; margin-bottom: 12pt;\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">A third model relies on technical auditing and traceability. In industrial data spaces such as the \u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Mobility Data Space\u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">, accountability is embedded in usage contracts between data providers and recipients and supported through technical infrastructure. The \u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Health Data Hub\u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"> uses a secure platform that traces actions performed on data, creating an audit trail for compliance. Within \u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">INSIGHT’s\u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"> Secure Research Environment, a data custodian must approve the export of analysis results to ensure that sensitive information does not leave the protected environment.\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp dir=\"ltr\" style=\"line-height: 1.38; margin-top: 12pt; margin-bottom: 12pt;\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Other initiatives ground accountability in ethical frameworks, standards, and training. \u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">The Language Data Commons of Australia\u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"> draws on CARE principles to support culturally appropriate stewardship of sensitive language data. \u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">INSIGHT \u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">uses the Five Safes framework to assess whether projects involve safe people, safe data, safe settings, safe outputs, and safe projects. \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp> \u003C\u002Fp>\n\u003Ch1 dir=\"ltr\" style=\"line-height: 1.38; margin-top: 14pt; margin-bottom: 4pt;\">\u003Cspan style=\"font-size: 15pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Reflections\u003C\u002Fspan>\u003C\u002Fh1>\n\u003Cp dir=\"ltr\" style=\"line-height: 1.38; margin-top: 12pt; margin-bottom: 12pt;\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Applying the assessment framework clarified that data commons are not simply repositories, platforms, or datasets, but socio-technical institutions. They must balance the needs of data providers, users, data subjects, affected communities, funders, and the broader public interest while sustaining the rules, relationships, and infrastructure that make responsible data access possible. \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp dir=\"ltr\" style=\"line-height: 1.38; margin-top: 12pt; margin-bottom: 12pt;\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">First, trust is essential. Across the repository, initiatives used access controls, accountability mechanisms, and ethical review to enable data access, especially where data is sensitive, culturally significant, commercially valuable, or personally identifiable. Secure research environments, public data-use registers, ethical review boards, contributor-controlled permissions, and traceable audit systems help create the conditions under which communities and institutions are willing to provide access.\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp dir=\"ltr\" style=\"line-height: 1.38; margin-top: 12pt; margin-bottom: 12pt;\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Second, data commons cannot depend on altruism alone. They require reciprocity. Contributors need meaningful value in return for the labor, risk, and expertise involved in preparing and sharing data. That value may come through access to a larger and better-curated shared resource, attribution, persistent identifiers, technical support, data enrichment, capacity-building, governance rights, or strategic influence. \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp dir=\"ltr\" style=\"line-height: 1.38; margin-top: 12pt; margin-bottom: 12pt;\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Third, grants, philanthropic support, public seed funding, and time-limited research funding can help launch initiatives, but they do not guarantee long-term sustainability. More durable initiatives combine funding sources such as public mandates, institutional support, membership dues, service fees, donations, volunteer labor, and consortium contributions. \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp dir=\"ltr\" style=\"line-height: 1.38; margin-top: 12pt; margin-bottom: 12pt;\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Finally, governance is the clearest boundary between a data commons and other forms of collaborative data sharing. Open datasets, data sharing platforms, standards bodies, and commons-enabling alliances can all contribute to the broader data ecosystem, but they do not automatically qualify as data commons. What matters is whether contributors, affected communities, members, or participating institutions hold meaningful authority over access rules, standards, stewardship practices, accountability mechanisms, or future development. This shared authority separates participation in building a data resource from participation in governing it as a commons. \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp dir=\"ltr\" style=\"line-height: 1.38; margin-top: 12pt; margin-bottom: 12pt;\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">***\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp dir=\"ltr\" style=\"line-height: 1.38; margin-top: 12pt; margin-bottom: 12pt;\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">To learn more about our broader data commons work, including the New Commons Incubator, visit \u003C\u002Fspan>\u003Ca style=\"text-decoration: none;\" href=\"http:\u002F\u002Fnewcommons.ai\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #1155cc; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: underline; -webkit-text-decoration-skip: none; text-decoration-skip-ink: none; vertical-align: baseline; white-space: pre-wrap;\">newcommons.ai\u003C\u002Fspan>\u003C\u002Fa>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">.  \u003C\u002Fspan>\u003C\u002Fp>",{},"what-our-repository-reveals-about-data-commons-in-the-ai-era","blogposts\u002Fwhat-our-repository-reveals-about-data-commons-in-the-ai-era","PMSSkisHeptYCHRYaTE6cN4CYJ288YY9PoqtdoQMDls",{"id":29,"brow":19,"cover_image":30,"date":31,"excerpt":9,"extension":10,"heading":32,"main_content":33,"meta":34,"slug":35,"stem":36,"tagline":9,"__hash__":37},"blogposts\u002Fblogposts\u002Fdefining-data-commons-a-framework-for-assessing-shared-data-resources.json","https:\u002F\u002Fcms.thegovlab.com\u002Fassets\u002F15a3a31b-d0a8-43c0-bd25-f5d10a485b4f","2026-07-06","Defining Data Commons: A Framework for Assessing Shared Data Resources","\u003Cp id=\"docs-internal-guid-4e206a0a-7fff-236d-b063-b9fe2aacf3a3\" dir=\"ltr\" style=\"line-height: 1.38; margin-top: 12pt; margin-bottom: 12pt;\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Actors around the world are turning to data commons to improve access to high-quality data for AI development while advancing more equitable, accountable, and collaborative approaches to data governance.\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp dir=\"ltr\" style=\"line-height: 1.38; margin-top: 12pt; margin-bottom: 12pt;\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">We define \u003C\u002Fspan>\u003Ca style=\"text-decoration: none;\" href=\"https:\u002F\u002Fincubator.opendatapolicylab.org\u002Ffiles\u002Fdata-commons-for-ai-blueprint.pdf\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #1155cc; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: underline; -webkit-text-decoration-skip: none; text-decoration-skip-ink: none; vertical-align: baseline; white-space: pre-wrap;\">data commons\u003C\u002Fspan>\u003C\u002Fa>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"> as collaboratively governed ecosystems that pool, steward, and provide responsible access to shared data resources. Yet initiatives operating under the label\u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: italic; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"> \u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">vary considerably in their governance structures, access models, funding arrangements, and relationships with contributors and affected communities. At the same time, many initiatives that resemble data commons in practice do not describe themselves using the term. Distinguishing data commons from adjacent models such as open data platforms, data cooperatives, or AI data pools is therefore not always straightforward. \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp dir=\"ltr\" style=\"line-height: 1.38; margin-top: 12pt; margin-bottom: 12pt;\"> \u003C\u002Fp>\n\u003Cp dir=\"ltr\" style=\"line-height: 1.38; margin-top: 12pt; margin-bottom: 12pt;\">\u003Cspan style=\"font-size: 13.999999999999998pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">What We Did \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp dir=\"ltr\" style=\"line-height: 1.38; margin-top: 12pt; margin-bottom: 12pt;\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">To better understand this landscape, the Open Data Policy Lab created the \u003C\u002Fspan>\u003Ca style=\"text-decoration: none;\" href=\"https:\u002F\u002Fdocs.google.com\u002Fspreadsheets\u002Fd\u002F1GPzU4Pspi-XOmJU13LvOUUPxtfTuRXcZMBw7lxkQRyY\u002Fedit?gid=0#gid=0\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #1155cc; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: underline; -webkit-text-decoration-skip: none; text-decoration-skip-ink: none; vertical-align: baseline; white-space: pre-wrap;\">Data Commons for Generative AI Repository\u003C\u002Fspan>\u003C\u002Fa>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">, which currently contains 49 initiatives spanning health, science, language, culture, mobility, environment, and other domains. The repository was developed through desk research and built on insights from our data commons work over the last two years, including research projects, studios, and the \u003C\u002Fspan>\u003Ca style=\"text-decoration: none;\" href=\"https:\u002F\u002Fwww.newcommons.ai\u002F\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #1155cc; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: underline; -webkit-text-decoration-skip: none; text-decoration-skip-ink: none; vertical-align: baseline; white-space: pre-wrap;\">New Commons Challenge\u003C\u002Fspan>\u003C\u002Fa>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">. In assembling it, we adopted a deliberately broad approach, capturing mature commons, federated infrastructures, cooperative models, consortium-based initiatives, and commons in development. \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp dir=\"ltr\" style=\"line-height: 1.38; margin-top: 12pt; margin-bottom: 12pt;\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">As the repository expanded, we needed a consistent way to assess how closely different initiatives aligned with the principles of a data commons. Drawing on our research and the characteristics identified through our work on data commons, including the principles outlined in our \u003C\u002Fspan>\u003Ca style=\"text-decoration: none;\" href=\"https:\u002F\u002Fincubator.opendatapolicylab.org\u002Ffiles\u002Fdata-commons-for-ai-blueprint.pdf\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #1155cc; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: underline; -webkit-text-decoration-skip: none; text-decoration-skip-ink: none; vertical-align: baseline; white-space: pre-wrap;\">Blueprint to Unlock Data Commons for AI\u003C\u002Fspan>\u003C\u002Fa>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">, we developed an assessment checklist. The checklist translates these characteristics into a set of elements that can be used to compare initiatives and evaluate how closely they align with the data commons model.\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp dir=\"ltr\" style=\"line-height: 1.38; margin-top: 12pt; margin-bottom: 12pt;\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">We reviewed each initiative against the checklist using desk research. We did not use the framework as a scoring system, and inclusion in the repository did not depend on meeting a fixed number of criteria. Nor did we expect every initiative to fully implement all six elements. Instead, we evaluated how initiatives approached each element and whether, taken together, they demonstrated characteristics consistent with a data commons. \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp dir=\"ltr\" style=\"line-height: 1.38; margin-top: 12pt; margin-bottom: 12pt;\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">After removing initiatives that no longer appeared active, we excluded initiatives when we found no evidence that contributors, affected communities, or member institutions could influence stewardship, access rules, accountability processes, or future development. Recognizing that the field remains at an early stage, we retained some commons-in-development that had not yet fully implemented governance or accountability structures when there was credible evidence that they were actively building toward them. \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp dir=\"ltr\" style=\"line-height: 1.38; margin-top: 12pt; margin-bottom: 12pt;\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Our objective was to reflect the diversity of institutional arrangements emerging across sectors while maintaining meaningful boundaries around the concept of a data commons.\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp> \u003C\u002Fp>\n\u003Cp dir=\"ltr\" style=\"line-height: 1.38; margin-top: 12pt; margin-bottom: 12pt;\">\u003Cspan style=\"font-size: 13.999999999999998pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">What We Developed: Six Elements of a Data Commons \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp dir=\"ltr\" style=\"line-height: 1.38; margin-top: 12pt; margin-bottom: 12pt;\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">These elements represent characteristics commonly found in data commons and provide a practical framework for assessment:\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cul style=\"margin-top: 0; margin-bottom: 0; padding-inline-start: 48px;\">\n\u003Cli dir=\"ltr\" style=\"list-style-type: disc; font-size: 11pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre;\" aria-level=\"1\">\n\u003Cp dir=\"ltr\" style=\"line-height: 1.38; margin-top: 12pt; margin-bottom: 0pt;\" role=\"presentation\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Public Purpose:\u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"> Whether the initiative aims to supply data needed to address public problems and support public-interest AI;\u003C\u002Fspan>\u003C\u002Fp>\n\u003C\u002Fli>\n\u003Cli dir=\"ltr\" style=\"list-style-type: disc; font-size: 11pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre;\" aria-level=\"1\">\n\u003Cp dir=\"ltr\" style=\"line-height: 1.38; margin-top: 0pt; margin-bottom: 0pt;\" role=\"presentation\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Contributor Benefits:\u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"> Whether contributors receive meaningful value in exchange for providing access to data, expertise, labor, or other resources;\u003C\u002Fspan>\u003C\u002Fp>\n\u003C\u002Fli>\n\u003Cli dir=\"ltr\" style=\"list-style-type: disc; font-size: 11pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre;\" aria-level=\"1\">\n\u003Cp dir=\"ltr\" style=\"line-height: 1.38; margin-top: 0pt; margin-bottom: 0pt;\" role=\"presentation\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Funding and Support: \u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Whether the initiative has identifiable sources of financial, institutional, technical, or operational support to sustain the commons over time;\u003C\u002Fspan>\u003C\u002Fp>\n\u003C\u002Fli>\n\u003Cli dir=\"ltr\" style=\"list-style-type: disc; font-size: 11pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre;\" aria-level=\"1\">\n\u003Cp dir=\"ltr\" style=\"line-height: 1.38; margin-top: 0pt; margin-bottom: 0pt;\" role=\"presentation\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Access Controls:\u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"> Whether the initiative establishes clear rules and mechanisms governing who can access data, under what conditions, and for what purposes;\u003C\u002Fspan>\u003C\u002Fp>\n\u003C\u002Fli>\n\u003Cli dir=\"ltr\" style=\"list-style-type: disc; font-size: 11pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre;\" aria-level=\"1\">\n\u003Cp dir=\"ltr\" style=\"line-height: 1.38; margin-top: 0pt; margin-bottom: 0pt;\" role=\"presentation\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Participatory Governance:\u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"> Whether contributors, affected communities, members, or participating institutions can meaningfully influence stewardship, rules, standards, or future development;\u003C\u002Fspan>\u003C\u002Fp>\n\u003C\u002Fli>\n\u003Cli dir=\"ltr\" style=\"list-style-type: disc; font-size: 11pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre;\" aria-level=\"1\">\n\u003Cp dir=\"ltr\" style=\"line-height: 1.38; margin-top: 0pt; margin-bottom: 12pt;\" role=\"presentation\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Accountability Mechanisms:\u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"> Whether the initiative includes safeguards, oversight processes, transparency measures, or other mechanisms that support responsible data use.\u003C\u002Fspan>\u003C\u002Fp>\n\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Cp dir=\"ltr\" style=\"line-height: 1.38; text-align: center; margin-top: 12pt; margin-bottom: 12pt;\">\u003Cimg src=\"https:\u002F\u002Fcms.thegovlab.com\u002Fassets\u002F483b0c62-9f86-4094-a03b-59ea6b431dae.png?width=372&height=414\" alt=\"Screenshot 2026 07 06 101135\">\u003C\u002Fp>\n\u003Cp dir=\"ltr\" style=\"line-height: 1.38; margin-top: 12pt; margin-bottom: 12pt;\">\u003Cspan style=\"font-size: 13.999999999999998pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">What We Found \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp dir=\"ltr\" style=\"line-height: 1.38; margin-top: 12pt; margin-bottom: 12pt;\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Across the repository, the vast majority of initiatives were created to serve a public purpose, offered clear benefits to contributors, had identifiable funding or support, and included some form of access control. Participatory governance and accountability mechanisms showed greater variation and ultimately became the most important criteria for distinguishing data commons from adjacent models. \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp dir=\"ltr\" style=\"line-height: 1.38; margin-top: 12pt; margin-bottom: 12pt;\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">The review process clarified several categories that should not automatically be treated as data commons. These included:\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cul style=\"margin-top: 0; margin-bottom: 0; padding-inline-start: 48px;\">\n\u003Cli dir=\"ltr\" style=\"list-style-type: disc; font-size: 11pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre;\" aria-level=\"1\">\n\u003Cp dir=\"ltr\" style=\"line-height: 1.38; margin-top: 12pt; margin-bottom: 0pt;\" role=\"presentation\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Centralized institutional or government-run platforms \u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">with no evidence of shared governance, community authority, or contributor stewardship;\u003C\u002Fspan>\u003C\u002Fp>\n\u003C\u002Fli>\n\u003Cli dir=\"ltr\" style=\"list-style-type: disc; font-size: 11pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre;\" aria-level=\"1\">\n\u003Cp dir=\"ltr\" style=\"line-height: 1.38; margin-top: 0pt; margin-bottom: 0pt;\" role=\"presentation\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Open datasets or one-time data publications \u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">lacking ongoing governance, stewardship, or accountability;\u003C\u002Fspan>\u003C\u002Fp>\n\u003C\u002Fli>\n\u003Cli dir=\"ltr\" style=\"list-style-type: disc; font-size: 11pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre;\" aria-level=\"1\">\n\u003Cp dir=\"ltr\" style=\"line-height: 1.38; margin-top: 0pt; margin-bottom: 0pt;\" role=\"presentation\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Peer-production, crowdsourcing, or co-production initiatives\u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"> where participants contribute data or labor without meaningful governance authority; and \u003C\u002Fspan>\u003C\u002Fp>\n\u003C\u002Fli>\n\u003Cli dir=\"ltr\" style=\"list-style-type: disc; font-size: 11pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre;\" aria-level=\"1\">\n\u003Cp dir=\"ltr\" style=\"line-height: 1.38; margin-top: 0pt; margin-bottom: 12pt;\" role=\"presentation\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Alliances, standards bodies, or coordination networks\u003C\u002Fspan>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"> that support data sharing but do not directly steward a shared data resource.\u003C\u002Fspan>\u003C\u002Fp>\n\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Cp dir=\"ltr\" style=\"line-height: 1.38; margin-top: 12pt; margin-bottom: 12pt;\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Many excluded initiatives exhibited openness, collaboration, or stakeholder engagement, but lacked mechanisms for shared stewardship and decision-making. The presence of a shared data resource alone was not sufficient; governance authority also needed to be distributed beyond a single central actor.\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp> \u003C\u002Fp>\n\u003Cp dir=\"ltr\" style=\"line-height: 1.38; margin-top: 12pt; margin-bottom: 12pt;\">\u003Cspan style=\"font-size: 13.999999999999998pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Looking Forward \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp dir=\"ltr\" style=\"line-height: 1.38; margin-top: 12pt; margin-bottom: 12pt;\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">This framework is not intended to provide an exhaustive answer to how a data commons should be constituted. It provides a practical way to examine emerging models, compare institutional approaches, and draw clearer distinctions within an evolving field. As data commons continue to emerge across sectors and geographies, the framework can help practitioners, researchers, policymakers, and funders better understand how different models approach governance, participation, accountability, and sustainability. \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp dir=\"ltr\" style=\"line-height: 1.38; margin-top: 12pt; margin-bottom: 12pt;\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">In our next post, we apply this framework across the repository and explore what it reveals about the current landscape of data commons. \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp dir=\"ltr\" style=\"line-height: 1.38; margin-top: 12pt; margin-bottom: 12pt;\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">***\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp> \u003C\u002Fp>\n\u003Cp dir=\"ltr\" style=\"line-height: 1.38; margin-top: 12pt; margin-bottom: 12pt;\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">To learn more about our broader data commons work, including the New Commons Incubator, visit \u003C\u002Fspan>\u003Ca style=\"text-decoration: none;\" href=\"http:\u002F\u002Fnewcommons.ai\">\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #1155cc; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: underline; -webkit-text-decoration-skip: none; text-decoration-skip-ink: none; vertical-align: baseline; white-space: pre-wrap;\">newcommons.ai\u003C\u002Fspan>\u003C\u002Fa>\u003Cspan style=\"font-size: 11pt; font-family: 'Proxima Nova',sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">.  \u003C\u002Fspan>\u003C\u002Fp>",{},"defining-data-commons-a-framework-for-assessing-shared-data-resources","blogposts\u002Fdefining-data-commons-a-framework-for-assessing-shared-data-resources","EPn7lZDbgdlluoWkFMAiiZ-uOfzODRJrXPIlpy7n-tA",{"id":39,"brow":40,"cover_image":41,"date":42,"excerpt":9,"extension":10,"heading":43,"main_content":44,"meta":45,"slug":46,"stem":47,"tagline":9,"__hash__":48},"blogposts\u002Fblogposts\u002Fnew-resource-data-commons-faq.json","Resource","https:\u002F\u002Fcms.thegovlab.com\u002Fassets\u002Fc75f4486-f070-4283-852b-7375befad4ea","2026-06-30","New Resource: Data Commons FAQ","\u003Cp dir=\"ltr\">What are data commons? Where did the concept come from? How are they different from other data collaboratives? What value do they provide? And what are there limitations?\u003C\u002Fp>\n\u003Cp dir=\"ltr\">These are just a few of the questions that we’ve received since The Open Data Policy Lab published its \u003Ca href=\"https:\u002F\u002Fincubator.opendatapolicylab.org\u002Ffiles\u002Fdata-commons-for-ai-blueprint.pdf\">Blueprint to Unlock New Data Commons for AI\u003C\u002Fa>—a framework for creating new, collaboratively governed data ecosystems that pool and provide responsible access to diverse, high-quality datasets from one or more sectors.\u003C\u002Fp>\n\u003Cp dir=\"ltr\">\u003Ca href=\"https:\u002F\u002Fnewcommons.ai\u002Fdocs\u002Fdata-commons-faq.pdf\">Data Commons: Frequently Asked Questions\u003C\u002Fa> seeks to answer some of those concerns. In the form of a short, 15-page report, it provides an overview of the concept and why they can serve as an alternative to the growing use of privatized data silos or extractive re-use of open datasets. It answers questions such as:\u003C\u002Fp>\n\u003Cul>\n\u003Cli dir=\"ltr\" aria-level=\"1\">\n\u003Cp dir=\"ltr\" role=\"presentation\">What is a data commons?\u003C\u002Fp>\n\u003C\u002Fli>\n\u003Cli dir=\"ltr\" aria-level=\"1\">\n\u003Cp dir=\"ltr\" role=\"presentation\">Where does the idea for a commons come from?\u003C\u002Fp>\n\u003C\u002Fli>\n\u003Cli dir=\"ltr\" aria-level=\"1\">\n\u003Cp dir=\"ltr\" role=\"presentation\">How are commons managed?\u003C\u002Fp>\n\u003C\u002Fli>\n\u003Cli dir=\"ltr\" aria-level=\"1\">\n\u003Cp dir=\"ltr\" role=\"presentation\">How are data commons different from data collaboratives?\u003C\u002Fp>\n\u003C\u002Fli>\n\u003Cli dir=\"ltr\" aria-level=\"1\">\n\u003Cp dir=\"ltr\" role=\"presentation\">What are some of the critiques of data commons?\u003C\u002Fp>\n\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Cp dir=\"ltr\">Authored by Stefaan Verhulst (The Govlab), Andrew J. Zahuranec (The GovLab), Hannah Chafetz (The GovLab), Leona Verdadero (UNESCO), and Jennifer Hansen (Microsoft), the resource is a vital component to the \u003Ca href=\"https:\u002F\u002Fnewcommons.ai\u002F\">New Commons Incubator\u003C\u002Fa>—which seeks applicants for a six-month capacity-building program to support the development of data commons proposals. \u003C\u002Fp>\n\u003Cp dir=\"ltr\">By reviewing the document, possible applicants can understand exactly what the Incubator seeks to achieve. Others can use the FAQ to guide their own work, developing data commons that correspond to the latest research and analysis. It is also available in \u003Ca href=\"https:\u002F\u002Fnewcommons.ai\u002Fdocs\u002Fdata-commons-faq-fr.pdf\">French\u003C\u002Fa> and \u003Ca href=\"https:\u002F\u002Fnewcommons.ai\u002Fdocs\u002Fdata-commons-faq-es.pdf\">Spanish\u003C\u002Fa>.\u003C\u002Fp>\n\u003Cp dir=\"ltr\">We invite you to read \u003Ca href=\"https:\u002F\u002Fnewcommons.ai\u002Fdocs\u002Fdata-commons-faq.pdf\">Data Commons: Frequently Asked Questions\u003C\u002Fa> to learn more about this work. If you have any questions, please feel free to contact us at \u003Ca href=\"mailto:newcommons@opendatapolicylab.org\">newcommons@opendatapolicylab.org\u003C\u002Fa>. \u003C\u002Fp>",{},"new-resource-data-commons-faq","blogposts\u002Fnew-resource-data-commons-faq","ozul3dNu9G9sR_s-xMimijVqC4zMe5UtQh-hBKmCv44",{"id":50,"brow":51,"cover_image":52,"date":53,"excerpt":9,"extension":10,"heading":54,"main_content":55,"meta":56,"slug":57,"stem":58,"tagline":9,"__hash__":59},"blogposts\u002Fblogposts\u002Fnew-commons-incubator-launches-to-support-indigenous-led-language-and-cultural-data-commons-in-the-age-of-ai.json","Announcement","https:\u002F\u002Fcms.thegovlab.com\u002Fassets\u002Ff287f8cf-3b13-4ec2-9208-626456b3fc7d","2026-06-18","New Commons Incubator Launches to Support Indigenous-Led Language and Cultural Data Commons in the Age of AI","\u003Cp dir=\"ltr\">NEW YORK CITY, NEW YORK — As artificial intelligence increasingly relies on language and cultural data, Indigenous communities face unprecedented opportunities and significant risks. While Indigenous languages and cultural knowledge can help shape more inclusive digital futures, too often communities have limited influence over how their data is collected, governed, used, or shared.\u003C\u002Fp>\n\u003Cp dir=\"ltr\">To address this challenge, The GovLab, Microsoft, and UNESCO are launching the \u003Ca href=\"https:\u002F\u002Fnewcommons.ai\u002F\">New Commons Incubator for Indigenous Languages and Culture\u003C\u002Fa>, a new initiative designed to support Indigenous-led efforts to develop data commons that preserve, steward, and responsibly govern language and cultural resources in the AI era.\u003C\u002Fp>\n\u003Cp dir=\"ltr\">\u003Ca href=\"https:\u002F\u002Fincubator.opendatapolicylab.org\u002Ffiles\u002Fdata-commons-for-ai-blueprint.pdf\">Data commons\u003C\u002Fa> are shared governance frameworks that enable communities to collectively decide how their data is managed, accessed, and used while ensuring that benefits flow back to the communities themselves. By supporting the development of Indigenous-led data commons, the Incubator seeks to strengthen community agency, support language revitalization, and ensure that Indigenous peoples can participate in shaping the future of AI on their own terms.\u003C\u002Fp>\n\u003Cp dir=\"ltr\">The Incubator is a capacity-building initiative that provides mentorship, training, technical guidance, and proposal development support. Participants will receive an in-person opportunity to collaborate and network with other participants, followed by six months of workshops, one-on-one clinics, expert mentorships, and peer learning opportunities. The program is designed to help teams prepare stronger proposals and will end with a final showcase where participants present these to potential funders, partners, and collaborators.\u003C\u002Fp>\n\u003Cp dir=\"ltr\">The goal is not to create data commons directly but to equip Indigenous innovators and communities with the tools, governance frameworks, partnerships, and implementation strategies needed to transform promising ideas into actionable and fundable initiatives.\u003C\u002Fp>\n\u003Cp>\u003Cstrong> \u003C\u002Fstrong>\u003C\u002Fp>\n\u003Ch3 dir=\"ltr\">Building on Past Success\u003C\u002Fh3>\n\u003Cp dir=\"ltr\">The Incubator builds upon the success of the \u003Ca href=\"https:\u002F\u002Fwww.newcommons.ai\u002Fblog\u002Fadvancing-data-governance-for-ai-innovation-insights-from-the-2025-new-commons-challenge-event\">2025 New Commons Challenge\u003C\u002Fa>, a global effort to advance new models of data stewardship and collective governance.\u003C\u002Fp>\n\u003Cp dir=\"ltr\">The Challenge attracted more than 175 submissions from around the world, revealing a growing demand for approaches that enable communities to govern and benefit from their own data. A significant number of proposals focused on Indigenous languages and cultural knowledge, highlighting both the urgency of preservation and the opportunity to ensure these resources are stewarded responsibly in the age of AI.\u003C\u002Fp>\n\u003Cp dir=\"ltr\">Many proposals demonstrated tremendous promise but required additional support to become operational, sustainable, and investment-ready. The New Commons Incubator was created to address that need by helping participants refine governance models, strengthen technical and organizational foundations, and develop implementation roadmaps capable of attracting long-term support.\u003C\u002Fp>\n\u003Cp dir=\"ltr\">The initiative also contributes to the goals of the \u003Ca href=\"https:\u002F\u002Fwww.unesco.org\u002Fen\u002Fdecades\u002Findigenous-languages\">International Decade of Indigenous Languages\u003C\u002Fa> (2022–2032), which seeks to preserve, revitalize, and promote Indigenous languages worldwide.\u003C\u002Fp>\n\u003Cp>\u003Cstrong> \u003C\u002Fstrong>\u003C\u002Fp>\n\u003Ch3 dir=\"ltr\">Calling interested communities to apply\u003C\u002Fh3>\n\u003Cp dir=\"ltr\">The Incubator begins with an open call for applications running from June 18 to August 14, 2026.\u003C\u002Fp>\n\u003Cp dir=\"ltr\">Applications must be Indigenous-led, demonstrate institutional or community support, and have a clear commitment to ensuring that benefits generated through the initiative are shared with Indigenous communities.\u003C\u002Fp>\n\u003Cp dir=\"ltr\">Interested applicants will submit concept notes outlining their vision, use case, and governance approach. Submissions will be reviewed by an international panel of Indigenous experts and leaders according to four criteria:\u003C\u002Fp>\n\u003Cul>\n\u003Cli dir=\"ltr\" aria-level=\"1\">\n\u003Cp dir=\"ltr\" role=\"presentation\">\u003Cstrong>Opportunity\u003C\u002Fstrong>: What challenge or use case does the proposal address?\u003C\u002Fp>\n\u003C\u002Fli>\n\u003Cli dir=\"ltr\" aria-level=\"1\">\n\u003Cp dir=\"ltr\" role=\"presentation\">\u003Cstrong>Community Relevance\u003C\u002Fstrong>: How does the initiative serve Indigenous communities and priorities?\u003C\u002Fp>\n\u003C\u002Fli>\n\u003Cli dir=\"ltr\" aria-level=\"1\">\n\u003Cp dir=\"ltr\" role=\"presentation\">\u003Cstrong>Resources and Readiness\u003C\u002Fstrong>: What assets, partnerships, and capabilities are available to support implementation?\u003C\u002Fp>\n\u003C\u002Fli>\n\u003Cli dir=\"ltr\" aria-level=\"1\">\n\u003Cp dir=\"ltr\" role=\"presentation\">\u003Cstrong>Team\u003C\u002Fstrong>: Who will participate in and lead the work?\u003C\u002Fp>\n\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Cp dir=\"ltr\">Five to six teams will be selected to participate in the Incubator and receive dedicated support over several months to transform their concepts into robust and actionable proposals.\u003C\u002Fp>\n\u003Ch3 dir=\"ltr\">A Coalition of Support\u003C\u002Fh3>\n\u003Cp dir=\"ltr\">The New Commons Incubator is made possible through the support of The GovLab, Microsoft, and UNESCO, together with a global steering committee of Indigenous leaders, practitioners, and experts.\u003C\u002Fp>\n\u003Cp dir=\"ltr\">Stefaan Verhulst, Co-Founder and Chief Research and Development Officer of The GovLab, said:\u003C\u002Fp>\n\u003Cp dir=\"ltr\">\u003Cem>\"For too long, communities have been asked to contribute data without having meaningful influence over how that data is used, governed, or who benefits from it. The New Commons Incubator is about moving from extraction to stewardship and from participation to agency. We want Indigenous communities to help shape the future of AI, not simply be subjects of it. By supporting Indigenous-led data commons, we hope to advance new models of digital self-determination that ensure languages, cultural knowledge, and community priorities remain at the center of technological innovation.\"\u003C\u002Fem>\u003C\u002Fp>\n\u003Cp dir=\"ltr\">Guilherme Canela de Souza Godoi, Director of the Division for Digital Inclusion, Policies and Transformation at UNESCO, added:\u003C\u002Fp>\n\u003Cp dir=\"ltr\">\u003Cem>\"This initiative advances the objectives of the International Decade of Indigenous Languages by co-creating tools with Indigenous communities and supporting them to steward their own linguistic and cultural resources. Ensuring that communities can govern and benefit from their own data is essential to preserving cultural diversity and fostering inclusive digital transformation.\"\u003C\u002Fem>\u003C\u002Fp>\n\u003Cp dir=\"ltr\">Jennifer Hansen, Director, Data Policy & Strategy, Microsoft\u003C\u002Fp>\n\u003Cp dir=\"ltr\">\u003Cem>\"We are proud to build on the success of last year's New Commons Challenge with an initiative specifically focused on Indigenous languages and cultures. We believe communities should have meaningful opportunities to steward and benefit from the data that increasingly shapes AI systems, and we look forward to supporting innovative Indigenous-led approaches that advance those goals.\"\u003C\u002Fem>\u003C\u002Fp>\n\u003Cp dir=\"ltr\">Steering Committee member Chantal Kamgne, Head of Research, EngageAfricaNLP and Managing Director, Localizzz, said: \u003C\u002Fp>\n\u003Cp dir=\"ltr\">\u003Cem>“For communities in indigenous, low-resourced and underserved contexts, technologies can support access to knowledge, services, safety, and opportunity. However, Indigenous languages’ place in AI should not be guided or decided by dataset builders or developers alone, but by the people who speak them and live through them. Giving those communities governance, consent, and control in how their languages enter digital spaces and technology means creating processes and protocols that listen before they collect, model, or use language data. The Indigenous Language and Culture Data Commons Incubator works toward exactly that: technology that is more inclusive without stripping languages of the cultural codes, meaning, identities and values that make them worth preserving.”\u003C\u002Fem>\u003C\u002Fp>\n\u003Cp dir=\"ltr\">From a separate Steering Committee Member, Jenny Fewster, Director, Humanities, Arts, Social Sciences and Indigenous Research Data Commons, Australian Research Data Commons:\u003C\u002Fp>\n\u003Cp dir=\"ltr\">\u003Cem>“The Commons Incubator is important because it creates a space where communities, researchers, and infrastructure providers can work together to ensure that emerging technologies strengthen, rather than diminish, Indigenous authority over language and cultural knowledge. Supporting Indigenous data commons is not just about preserving the past, it is about creating the conditions for Indigenous languages, cultures, and knowledge systems to thrive into the future.\"\u003C\u002Fem>\u003C\u002Fp>\n\u003Cp dir=\"ltr\">\u003Cstrong>Join the Incubator\u003C\u002Fstrong>\u003C\u002Fp>\n\u003Cp dir=\"ltr\">Applications for the New Commons Incubator open on June 18, 2026.\u003C\u002Fp>\n\u003Cp dir=\"ltr\">Interested participants can find more information, including eligibility criteria, program details, and governance documentation, at \u003Ca href=\"http:\u002F\u002Fnewcommons.ai\">newcommons.ai\u003C\u002Fa>\u003C\u002Fp>\n\u003Cp dir=\"ltr\">For inquiries, contact \u003Ca href=\"mailto:contactnewcommons@opendatapolicylab.org\">contactnewcommons@opendatapolicylab.org\u003C\u002Fa>\u003C\u002Fp>\n\u003Cp dir=\"ltr\">\u003Cem>The New Commons Incubator seeks not only to support individual projects, but also to advance a broader vision of digital self-determination; one in which Indigenous communities collectively govern the data, knowledge, and cultural resources that increasingly shape our shared digital future.\u003C\u002Fem>\u003C\u002Fp>",{},"new-commons-incubator-launches-to-support-indigenous-led-language-and-cultural-data-commons-in-the-age-of-ai","blogposts\u002Fnew-commons-incubator-launches-to-support-indigenous-led-language-and-cultural-data-commons-in-the-age-of-ai","e-cS8RKfVoDHub5wbazHn8mfSK-_5OP06eQE5aXkB0U",{"id":61,"brow":62,"cover_image":63,"date":64,"excerpt":9,"extension":10,"heading":65,"main_content":66,"meta":67,"slug":68,"stem":69,"tagline":9,"__hash__":70},"blogposts\u002Fblogposts\u002Fadvancing-data-governance-for-ai-innovation-insights-from-the-2025-new-commons-challenge-event.json","Blog Post","https:\u002F\u002Fcms.thegovlab.com\u002Fassets\u002F6b3ea4ea-0679-43f0-a266-148da15ab830","2025-10-09","Advancing Data Governance for AI Innovation: Insights from the 2025 New Commons Challenge Event","\u003Cp dir=\"ltr\">In today’s data-driven world, the promise of artificial intelligence for the public good depends not just on algorithms, but on the quality and governance of the data they rely upon. For communities facing crises—whether for disaster response, public health, or local planning—the right data can enable faster, fairer, and more accountable decision-making. \u003C\u002Fp>\n\u003Cp dir=\"ltr\">Yet too often, this information remains siloed, fragmented, or inaccessible. The idea of data commons offers a way forward: Pooling datasets under shared governance to ensure that AI innovation is not only technically sound, but also trustworthy, equitable, and aligned with community needs.\u003C\u002Fp>\n\u003Cp dir=\"ltr\">On September 25th, 2025—at an event in New York City—the \u003Ca href=\"https:\u002F\u002Fopendatapolicylab.org\u002F\">Open Data Policy Lab\u003C\u002Fa>, in collaboration with \u003Ca href=\"https:\u002F\u002Fwww.microsoft.com\u002Fen-us\u002F\">Microsoft\u003C\u002Fa> and in partnership with \u003Ca href=\"https:\u002F\u002Fwww.directrelief.org\u002F?utm_source=google&utm_medium=cpc&utm_campaign=Branded&gad_source=1&gad_campaignid=627399536&gbraid=0AAAAADEzrS_btF6ocIyLHfCS9Vxfc5vmk&gclid=Cj0KCQjw0NPGBhCDARIsAGAzpp3sz1KhR00FD9QvmxsQjXCTXjQBCrPiIHzKK2YU4MIQ4Vb6_WA8qZoaAuklEALw_wcB\">Direct Relief\u003C\u002Fa>\u002F\u003Ca href=\"https:\u002F\u002Fwww.crisisready.io\u002F\">CrisisReady\u003C\u002Fa> and the \u003Ca href=\"https:\u002F\u002Fhls.harvard.edu\u002Flibrary\u002Fabout-the-library\u002Flibrary-staff\u002Finstitutional-data-initiative\u002F\">Institutional Data Initiative at the Harvard Law School Library\u003C\u002Fa>, with serving \u003Ca href=\"https:\u002F\u002Fwww.unesco.org\u002Fen\">UNESCO\u003C\u002Fa> as an international observer, announced the winners of the \u003Ca href=\"https:\u002F\u002Fwww.newcommons.ai\u002F\">2025 New Commons Challenge\u003C\u002Fa>. The initiative awarded two projects $100,000 each to advance the creation of data commons that accelerate responsible AI innovation in disaster response and localized decision-making.\u003C\u002Fp>\n\u003Cp dir=\"ltr\">The event convened global leaders, policymakers, technologists, and community practitioners to explore how data sharing can unlock new opportunities for AI in the public interest. In what follows, we provide a summary of the winners and the discussions that took place during the event.\u003C\u002Fp>\n\u003Ch3 dir=\"ltr\">Opening Remarks: Building Data Commons for the Public Good\u003Cbr>\u003Cbr>\u003C\u002Fh3>\n\u003Ccenter>\u003Cimg src=\"https:\u002F\u002Fcms.thegovlab.com\u002Fassets\u002F180496d0-2ec1-4e7d-9b07-67acd4981c09.jpg?width=594&height=396\" alt=\"Teresa Hutson delivers opening remarks\">\u003C\u002Fcenter>\n\u003Cp dir=\"ltr\">Teresa Hutson, Corporate Vice President of Microsoft’s Trusted Technology Group, opened the event by underscoring the importance of diverse, high-quality data for responsible AI innovation. She noted that data is not inherently valuable on its own, it becomes impactful when responsibly shared and reused. Highlighting Microsoft’s Open Data campaign and collaborations with The GovLab, Harvard’s Institutional Data Initiative, and European-led projects, she emphasized the need to expand access to datasets that reflect cultural and linguistic diversity.\u003C\u002Fp>\n\u003Cp dir=\"ltr\">Despite this progress, Hutson cautioned that many AI models remain limited by biased or fragmented data, particularly in under-resourced languages and regions. She argued that the solution lies in developing data commons—shared pools of data governed for reuse, interoperability, and accountability. \u003C\u002Fp>\n\u003Cp dir=\"ltr\">Framing the New Commons Challenge as a step forward, she invited participants to see themselves as stewards of data that can fuel AI solutions for disaster response, localized decision-making, and the broader public good.\u003C\u002Fp>\n\u003Ch3 dir=\"ltr\">Framing the Challenge: Data Commons as Missing Infrastructure\u003Cbr>\u003Cbr>\u003C\u002Fh3>\n\u003Ccenter>\u003Cimg src=\"https:\u002F\u002Fcms.thegovlab.com\u002Fassets\u002F48b180df-b532-4bf3-9f76-d75402f61c4d.png?width=607&height=405\" alt=\"Stefaan delivers remarks on the New Commons Challenge Showcase\">\u003C\u002Fcenter>\n\u003Cp dir=\"ltr\">Stefaan Verhulst, Co-Founder and Chief Research and Development Officer of The GovLab, followed by setting the stage for the New Commons Challenge. He described data commons as the “missing infrastructure” for Public Interest AI—essential to scaling solutions for humanitarian response, local decision-making, and other pressing societal needs. \u003C\u002Fp>\n\u003Cp dir=\"ltr\">While the world is awash in data, much of it remains inaccessible or unusable for the public good. Data commons, he argued, provides both the governance and technical frameworks to make high-quality, context-specific data available in ways that respect community expectations. Without such commons, the promise of “AI for good” risks being limited or unsustainable.\u003C\u002Fp>\n\u003Cp dir=\"ltr\">He went on to explain how this realization led The GovLab, in partnership with Microsoft, Direct Relief\u002FCrisisReady, Harvard’s Institutional Data Initiative, and UNESCO, to launch the first-ever New Commons Challenge six months earlier. The goal was to identify and support pioneers advancing data commons in practice. \u003C\u002Fp>\n\u003Cp dir=\"ltr\">The response, he noted, was overwhelming: 170 applications from 51 countries, with more than 150 reviewed in detail and 44 invited for further consideration. From this process, two winners and several honorary mentions emerged—demonstrating that the idea of data commons is not abstract but already being built by a growing global community.\u003C\u002Fp>\n\u003Ch3 dir=\"ltr\">The Award Ceremony\u003Cbr>\u003Cbr>\u003C\u002Fh3>\n\u003Ccenter>\u003Cimg src=\"https:\u002F\u002Fcms.thegovlab.com\u002Fassets\u002Fff71ad2e-e26b-4b56-8916-782a9f3f9845.jpeg?width=554&height=739\" alt=\"The New Commons Challenge Awards\">\u003C\u002Fcenter>\n\u003Cp dir=\"ltr\">Following these remarks, Teresa and Stefaan announced the winners of the New Commons Challenge.\u003C\u002Fp>\n\u003Cp dir=\"ltr\">CERTI Amazônia Institute received the award for Enhancement of a Data Commons. Their Amazon Rainforest Evolution Index transforms environmental data into AI-ready tools to track deforestation and land-use change in Brazil’s Legal Amazon—a region covering nine states and roughly 61% of Brazil’s territory, empowering sustainable development decisions.\u003C\u002Fp>\n\u003Cp dir=\"ltr\">NYU Peace Research and Education Program is the award winner of the Development of a Data Commons category. Their initiative, Malawi Voice Data Commons, developed in collaboration with Ushahidi, UNDP, and Mozilla Foundation, enables rural Malawians to report emergencies in native languages, creating multilingual, AI-ready datasets for humanitarian response and language preservation. The pilot will take place in Malawi with plans to scale across Sub-Saharan Africa.\u003C\u002Fp>\n\u003Cp dir=\"ltr\">The two teams presented on their winning proposals and discussed how they would use the funding to support their data commons initiatives.\u003C\u002Fp>\n\u003Cp dir=\"ltr\">The Challenge also announced several honorable distinctions, including:\u003C\u002Fp>\n\u003Cul>\n\u003Cli dir=\"ltr\" aria-level=\"1\">\n\u003Cp dir=\"ltr\" role=\"presentation\">\u003Ca href=\"https:\u002F\u002Fwww.newcommons.ai\u002Fwinners\u002Fquerido-diario\">Open Knowledge Brazil’s Querido Diário\u003C\u002Fa>: Open Knowledge Brasil’s initiative converts municipal gazettes into AI-readable datasets, advancing transparency, civic oversight, and inclusive governance across Brazil.\u003C\u002Fp>\n\u003C\u002Fli>\n\u003Cli dir=\"ltr\" aria-level=\"1\">\n\u003Cp dir=\"ltr\" role=\"presentation\">\u003Ca href=\"https:\u002F\u002Fwww.newcommons.ai\u002Fwinners\u002Fknow-your-city-academy\">Slum Dwellers International’s Know Your City Academy\u003C\u002Fa>: Slum Dwellers International and Arkology Studio are building a data commons for 5,000+ informal settlements in 18 African countries, integrating oral histories and structured data to promote peer learning and inclusive data practices.\u003C\u002Fp>\n\u003C\u002Fli>\n\u003Cli dir=\"ltr\" aria-level=\"1\">\n\u003Cp dir=\"ltr\" role=\"presentation\">\u003Ca href=\"https:\u002F\u002Fwww.newcommons.ai\u002Fwinners\u002Fplace-hub-in-nigeria\">PLACE Foundation’s PLACE Hub in Nigeria\u003C\u002Fa>: Funded by ThisisPLACE, PLACE is replicating its proven model in other regions to Abuja, Nigeria to expand its community-driven spatial data infrastructure to enable responsible AI for urban planning, disaster response, and infrastructure development in Nigeria.   \u003C\u002Fp>\n\u003C\u002Fli>\n\u003Cli dir=\"ltr\" aria-level=\"1\">\n\u003Cp dir=\"ltr\" role=\"presentation\">\u003Ca href=\"https:\u002F\u002Fwww.newcommons.ai\u002Fwinners\u002Fadvancing-climate-justice-the-climate-mobility-case-database\">Global Strategic Litigation Council’s Advancing Climate Justice\u003C\u002Fa>: The Climate Mobility Case Database: Tens of millions are displaced annually by the climate crisis. The Climate Mobility Case Database uses AI to distill complex global case law on climate displacement into accessible, multilingual knowledge. By distilling lessons learned from courts across the world, this open platform equips communities, practitioners, and policymakers with the tools to defend rights, strengthen advocacy, and drive policy reform for at-risk and climate-displaced people worldwide. Developed by the Global Strategic Litigation Council, in collaboration with Earth Refuge, the Raoul Wallenberg Institute, and the Zolberg Institute.\u003C\u002Fp>\n\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Cp dir=\"ltr\">More information on each awardee and honored participant can be found \u003Ca href=\"https:\u002F\u002Fwww.newcommons.ai\u002Fblog\u002Fbuilding-the-future-of-public-interest-ai-certi-amazonia-institute-and-nyu-peace-research-announced-as-winners-of-the-new-commons-challenge\">here\u003C\u002Fa>.\u003C\u002Fp>\n\u003Ch3 dir=\"ltr\">Fireside Chat: Data Commons for AI Innovation and Global Impact\u003Cbr>\u003Cbr>\u003C\u002Fh3>\n\u003Ccenter>\u003Cimg src=\"https:\u002F\u002Fcms.thegovlab.com\u002Fassets\u002F9c7e9e71-3eab-4f9e-a2b8-c5a53db88638.jpg?width=607&height=405\" alt=\"The fireside chat with Isabel De Sola Criado\">\u003C\u002Fcenter>\n\u003Cp dir=\"ltr\">The award ceremony was then followed by a fireside chat between Stefaan G. Verhulst, Co-Founder and Chief Research and Development Officer of The GovLab, and Isabel De Sola Criado, Head of the Coordination Unit at the UN Office for Digital and Emerging Technologies. Their conversation explored how data commons can accelerate AI innovation, scale public-interest impact, and support global digital strategies. \u003C\u002Fp>\n\u003Cp dir=\"ltr\">Below is a summary of the main themes discussed.\u003C\u002Fp>\n\u003Ch4 dir=\"ltr\">(1) Data Commons as Global Infrastructure\u003C\u002Fh4>\n\u003Cp dir=\"ltr\">Verhulst opened the discussion by positioning data commons as the “missing infrastructure” for public interest AI. He emphasized their role in making high-quality, context-specific data accessible in ways that respect community expectations. Criado agreed, situating data commons within the broader framework of the UN’s Global Digital Compact (GDC), which she described as a milestone in renewing the global digital agenda. She highlighted that data governance—one of the GDC’s five pillars—explicitly references data commons as a tool for closing digital divides and preventing a future AI divide.\u003C\u002Fp>\n\u003Ch4 dir=\"ltr\">(2) The Global Digital Compact and Data Governance\u003C\u002Fh4>\n\u003Cp dir=\"ltr\">Criado explained that the GDC sets out interlocking priorities: bridging digital divides, strengthening the digital economy, promoting a safe and open online space, advancing data governance, and ensuring responsible AI. Data commons, she argued, are a concrete way to deliver on these goals, especially the fourth pillar on data governance. She noted that building ethical AI requires ethical data governance and that commons provide an example of how to manage data responsibly while creating broad societal value.\u003C\u002Fp>\n\u003Ch4 dir=\"ltr\">(3) Diverse Needs Across Member States\u003C\u002Fh4>\n\u003Cp dir=\"ltr\">Verhulst invited Criado to share what she hears from UN member states and civil society about the challenges of advancing data governance. She explained that needs vary widely depending on political, economic, and development contexts. Some countries focus on strengthening basic data infrastructure or passing privacy laws, while others grapple with capacity-building and accountability. Many developing states, she noted, feel overwhelmed by competing digital priorities, from connectivity to skills development, making the case for starting with strong data governance as a foundation for broader digital transformation.\u003C\u002Fp>\n\u003Ch4 dir=\"ltr\">(4) Aligning Data and AI Governance\u003C\u002Fh4>\n\u003Cp dir=\"ltr\">The discussion also highlighted the deep interconnection between data governance and AI governance. Verhulst stressed that AI governance cannot advance without solid systems for data access and oversight. Criado echoed this point, noting ongoing UN initiatives such as the Global Dialogue on AI Governance and the Secretary-General’s High-Level Advisory Body on AI. Both efforts recognize data commons as essential to ensuring that AI systems are equitable, transparent, and accountable.\u003C\u002Fp>\n\u003Ch4 dir=\"ltr\">(5) Incentives, Trust, and the Role of Intermediaries\u003C\u002Fh4>\n\u003Cp dir=\"ltr\">Criado concluded by underscoring the importance of incentives and trust in building sustainable data commons. She observed that organizations and governments often ask, “What’s in it for me?”—making it critical to clearly articulate the benefits of sharing data. Trusted intermediaries, she argued, can play a vital role in bringing diverse stakeholders together, ensuring decisions are made transparently and equitably. She also highlighted the need for commons that address urgent issues such as human rights, online safety, and protecting women and girls, noting that these areas remain underdeveloped despite their importance.\u003C\u002Fp>\n\u003Ch3 dir=\"ltr\">Closing Remarks: Celebrating Digital Progress and Partnerships\u003Cbr>\u003Cbr>\u003C\u002Fh3>\n\u003Ccenter>\u003Cimg src=\"https:\u002F\u002Fcms.thegovlab.com\u002Fassets\u002F4c5812ed-c0cc-4dba-81c6-4be5670fc545.png?width=607&height=405\" alt=\"Closing remarks of the New Commons Award Showcase\">\u003C\u002Fcenter>\n\u003Cp dir=\"ltr\">The event concluded with reflections from Alex Wong, Senior Advisor for Strategic Engagement and Initiatives at the International Telecommunication Union (ITU), and Robert Opp, Chief Digital Officer at the United Nations Development Programme (UNDP). Wong emphasized that amidst ongoing debates about governance risks, it is equally important to celebrate the power of digital innovation. \u003C\u002Fp>\n\u003Cp dir=\"ltr\">He pointed to the breadth of initiatives showcased during UNGA’s “Digital at UNGA” program—spanning agriculture, healthcare, youth, and climate change—as evidence of how technology is reshaping societies. He highlighted the New Commons Challenge as part of this momentum, underscoring the role of companies like Microsoft in committing significant new investments to AI skills and education.\u003C\u002Fp>\n\u003Cp dir=\"ltr\">Opp built on these reflections by stressing that data is the fundamental foundation of digital transformation. He noted that as countries invest in digital infrastructure, interoperability and trusted data governance are what make it possible to deliver better public services, inform policymaking, and foster private-sector innovation. In the AI era, he argued, this becomes even more critical: data must be accurate, representative, and responsibly governed for models to advance sustainable development safely. Opp closed by emphasizing the importance of collaboration and partnerships, highlighting how ITU and UNDP’s joint efforts demonstrate the value of combining technical expertise with a human development lens. He situated this work within a broader year of milestones—including the anniversaries of ITU, the UN, UNDP, and the World Summit on the Information Society—reminding participants that collective efforts today will shape the digital future for decades to come.\u003C\u002Fp>\n\u003Cp dir=\"ltr\">***\u003C\u002Fp>\n\u003Cp dir=\"ltr\">Have any questions or are interested in collaborating? Reach out to us at \u003Ca href=\"mailto:newcommons@opendatapolicylab.org\">newcommons@opendatapolicylab.org\u003C\u002Fa>. \u003C\u002Fp>",{},"advancing-data-governance-for-ai-innovation-insights-from-the-2025-new-commons-challenge-event","blogposts\u002Fadvancing-data-governance-for-ai-innovation-insights-from-the-2025-new-commons-challenge-event","tCPm39ciPEVZsbNxhzHGSVkb29UALbZV6eI35vKR0W0",{"id":72,"brow":73,"cover_image":74,"date":75,"excerpt":9,"extension":10,"heading":76,"main_content":77,"meta":78,"slug":79,"stem":80,"tagline":9,"__hash__":81},"blogposts\u002Fblogposts\u002Fbuilding-the-future-of-public-interest-ai-certi-amazonia-institute-and-nyu-peace-research-announced-as-winners-of-the-new-commons-challenge.json","Press Release","https:\u002F\u002Fcms.thegovlab.com\u002Fassets\u002Fb667ce08-93c5-4849-a1d4-6a42a9f2ebed","2025-09-26","Building the Future of Public-Interest AI: Certi Amazônia Institute and NYU Peace Research Announced as Winners of the New Commons Challenge","\u003Cp dir=\"ltr\">\u003Cstrong>New York, September 25, 2025\u003C\u002Fstrong>—Artificial Intelligence is only as good as the data it draws upon. For public-interest uses—from emergency response to localized decision making— high-quality, representative, and responsibly governed datasets are essential. Yet too often, the data needed for humanitarian interventions or local problem-solving is fragmented, inaccessible, or not aligned with community needs and expectations.\u003C\u002Fp>\n\u003Cp dir=\"ltr\">Data commons address this gap. By pooling datasets under clear governance rules — with shared purpose, stewardship, and safeguards — they create trusted infrastructure for responsible AI. Unlike ad-hoc data projects, commons are designed for reuse, interoperability, and accountability, ensuring that AI solutions are not just technically sound but also socially licensed.\u003C\u002Fp>\n\u003Cp style=\"margin-left: 40px;\">“The future of AI in the public interest depends on more than algorithms — it depends on the data we choose to share, how we govern that data, and whether communities see value in its reuse.” — Stefaan Verhulst, The GovLab\u003C\u002Fp>\n\u003Cp style=\"margin-left: 40px;\">“From disaster relief to public health, the fastest path to impact is making frontline data findable, trustworthy, and reusable.” — Andrew Schroeder, VP of Research & Analysis, Direct Relief\u003C\u002Fp>\n\u003Cp dir=\"ltr\">That is precisely the objective of the \u003Ca href=\"https:\u002F\u002Fwww.newcommons.ai\u002F'\">New Commons Challenge\u003C\u002Fa>: to accelerate the creation of data commons that fuel AI-driven solutions while respecting community expectations and maximizing public value.\u003C\u002Fp>\n\u003Cp dir=\"ltr\">The Challenge awards two initiatives with $100,000 each to develop data commons that fuel responsible AI innovation as it relates to disaster response and localized decision making. It is an initiative by the \u003Ca href=\"https:\u002F\u002Fopendatapolicylab.org\u002F\">Open Data Policy Lab\u003C\u002Fa> (a collaboration between Microsoft and The GovLab) and was conducted in partnership with \u003Ca href=\"https:\u002F\u002Fwww.directrelief.org\u002F\">Direct Relief\u003C\u002Fa>\u002F\u003Ca href=\"http:\u002F\u002Fcrisisready.io\">CrisisReady\u003C\u002Fa>, the \u003Ca href=\"https:\u002F\u002Fhls.harvard.edu\u002Flibrary\u002Fabout-the-library\u002Flibrary-staff\u002Finstitutional-data-initiative\u002F\">Institutional Data Initiative at the Harvard Law School Library\u003C\u002Fa> and \u003Ca href=\"https:\u002F\u002Fwww.unesco.org\u002Fen\">UNESCO\u003C\u002Fa> (international observer).\u003C\u002Fp>\n\u003Cp dir=\"ltr\">On Thursday, September 25th at an event in New York, the winners of the 2025 New Commons Challenge were announced. \u003C\u002Fp>\n\u003Cp dir=\"ltr\">Certi Amazônia Institute and NYU Peace Research and Education Program have been named as the winners of the New Commons Challenge: \u003C\u002Fp>\n\u003Cp dir=\"ltr\"> \u003C\u002Fp>\n\u003Ccenter>\u003Cimg src=\"https:\u002F\u002Fcms.thegovlab.com\u002Fassets\u002F2a37a334-8a50-40e7-876b-289be218afa3.jpg?width=729&height=486\" alt=\"Presentation on the Amazon Rainforest Presentation\">\u003C\u002Fcenter>\n\u003Cp> \u003C\u002Fp>\n\u003Cp dir=\"ltr\">CERTI Amazônia Institute received the award for Enhancement of a Data Commons. Their \u003Ca href=\"https:\u002F\u002Fwww.newcommons.ai\u002Fwinners\u002Famazon-rainforest-evolution-index\" target=\"_blank\" rel=\"noopener\">Amazon Rainforest Evolution Index\u003C\u002Fa> transforms environmental data into AI-ready tools to track deforestation and land-use change in Brazil’s Legal Amazon—a region covering nine states and roughly 61% of Brazil’s territory, empowering sustainable development decisions.\u003C\u002Fp>\n\u003Cp dir=\"ltr\">“The Amazon is changing before our eyes. With the Amazon Rainforest Evolution Index, we’re transforming disparate data into a shared commons that communities, scientists, and policymakers can all use. Our goal is to empower sustainable choices that protect both the forest and the people who depend on it.” — \u003Cem>Executive Director, CERTI Amazônia Institute\u003C\u002Fem>\u003C\u002Fp>\n\u003Ccenter>\u003Cem>\u003Cimg src=\"https:\u002F\u002Fcms.thegovlab.com\u002Fassets\u002Fcf41aa9a-3e6d-4a2b-b0eb-a0a946881eff.png?width=648&height=432\" alt=\"Presentation from the Malawi Voice Data Commons\">\u003C\u002Fem>\u003C\u002Fcenter>\n\u003Cp> \u003C\u002Fp>\n\u003Cp dir=\"ltr\">NYU Peace Research and Education Program is the award winner of the Development of a Data Commons category. Their initiative, \u003Ca href=\"https:\u002F\u002Fwww.newcommons.ai\u002Fwinners\u002Fmalawi-voice-data-commons\" target=\"_blank\" rel=\"noopener\">Malawi Voice Data Commons\u003C\u002Fa>, developed in collaboration with Ushahidi, UNDP, and Mozilla Foundation, enables rural Malawians to report emergencies in native languages, creating multilingual, AI-ready datasets for humanitarian response and language preservation. The pilot will take place in Malawi with plans to scale across Sub-Saharan Africa.\u003C\u002Fp>\n\u003Cp dir=\"ltr\">“When floods approach or violence erupts, language barriers can be deadly. The Malawi Voice Data Commons allows rural Malawians to report emergencies in their own languages while preserving cultural heritage. By making these voices AI-ready, we are ensuring that humanitarian response is faster and more inclusive.” — \u003Cem>Katerina Siira and Marine Collins Ragnet Co-Program Leads, NYU Peace Research and Education Program\u003C\u002Fem>\u003C\u002Fp>\n\u003Cp dir=\"ltr\">The \u003Ca href=\"https:\u002F\u002Fwww.newcommons.ai\u002Fprize\u002F#judges\">judges\u003C\u002Fa>, composed of diverse experts across technology, civil society, academia, and international organizations also provided four honorary distinctions. These included:\u003C\u002Fp>\n\u003Cp dir=\"ltr\">\u003Cem>\u003Cstrong>Development of a Data Commons:\u003C\u002Fstrong>\u003C\u002Fem>\u003C\u002Fp>\n\u003Cul>\n\u003Cli dir=\"ltr\" aria-level=\"1\">\n\u003Cp dir=\"ltr\" role=\"presentation\">\u003Cstrong>\u003Ca href=\"https:\u002F\u002Fwww.newcommons.ai\u002Fwinners\u002Fquerido-diario\" target=\"_blank\" rel=\"noopener\">Open Knowledge Brazil’s Querido Diário\u003C\u002Fa>: \u003C\u002Fstrong>Open Knowledge Brasil’s initiative converts municipal gazettes into AI-readable datasets, advancing transparency, civic oversight, and inclusive governance across Brazil.\u003C\u002Fp>\n\u003C\u002Fli>\n\u003Cli dir=\"ltr\" aria-level=\"1\">\n\u003Cp dir=\"ltr\" role=\"presentation\">\u003Cstrong>\u003Ca href=\"https:\u002F\u002Fwww.newcommons.ai\u002Fwinners\u002Fknow-your-city-academy\" target=\"_blank\" rel=\"noopener\">Slum Dwellers International’s Know Your City Academy\u003C\u002Fa>:\u003C\u002Fstrong> Slum Dwellers International and Arkology Studio are building a data commons for 5,000+ informal settlements in 18 African countries, integrating oral histories and structured data to promote peer learning and inclusive data practices.\u003C\u002Fp>\n\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Cp>\u003Cstrong> \u003C\u002Fstrong>\u003C\u002Fp>\n\u003Cp dir=\"ltr\">\u003Cstrong>\u003Cem>Enhancement of a Data Commons\u003C\u002Fem>\u003C\u002Fstrong>\u003C\u002Fp>\n\u003Cul>\n\u003Cli dir=\"ltr\" aria-level=\"1\">\n\u003Cp dir=\"ltr\" role=\"presentation\">\u003Cstrong>\u003Ca href=\"https:\u002F\u002Fwww.newcommons.ai\u002Fwinners\u002Fplace-hub-in-nigeria\" target=\"_blank\" rel=\"noopener\">PLACE Foundation’s PLACE Hub in Nigeria\u003C\u002Fa>: \u003C\u002Fstrong>Funded by ThisisPLACE, PLACE is replicating its proven model in other regions to Abuja, Nigeria to expand its community-driven spatial data infrastructure to enable responsible AI for urban planning, disaster response, and infrastructure development in Nigeria.   \u003C\u002Fp>\n\u003C\u002Fli>\n\u003Cli dir=\"ltr\" aria-level=\"1\">\n\u003Cp dir=\"ltr\" role=\"presentation\">\u003Cstrong>\u003Ca href=\"https:\u002F\u002Fwww.newcommons.ai\u002Fwinners\u002Fadvancing-climate-justice-the-climate-mobility-case-database\" target=\"_blank\" rel=\"noopener\">Global Strategic Litigation Council’s Advancing Climate Justice\u003C\u002Fa>: T\u003C\u002Fstrong>he Climate Mobility Case Database: Tens of millions are displaced annually by the climate crisis. The Climate Mobility Case Database uses AI to distill complex global case law on climate displacement into accessible, multilingual knowledge. By distilling lessons learned from courts across the world, this open platform equips communities, practitioners, and policymakers with the tools to defend rights, strengthen advocacy, and drive policy reform for at-risk and climate-displaced people worldwide. Developed by the Global Strategic Litigation Council, in collaboration with Earth Refuge, the Raoul Wallenberg Institute, and the Zolberg Institute.\u003Cstrong>\u003Cbr>\u003C\u002Fstrong>\u003C\u002Fp>\n\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Ch3 dir=\"ltr\">What’s Next\u003C\u002Fh3>\n\u003Cp dir=\"ltr\">The New Commons Challenge is not only about recognizing innovators — it is also about building a broader ecosystem for data commons. The next phase will include:\u003C\u002Fp>\n\u003Cul>\n\u003Cli dir=\"ltr\" aria-level=\"1\">\n\u003Cp dir=\"ltr\" role=\"presentation\">\u003Cstrong>Incubator Support: \u003C\u002Fstrong>Providing the winning teams with mentorship, technical assistance, and peer learning opportunities to refine and scale their data commons.\u003C\u002Fp>\n\u003C\u002Fli>\n\u003Cli dir=\"ltr\" aria-level=\"1\">\n\u003Cp dir=\"ltr\" role=\"presentation\">\u003Cstrong>Repository of Examples: \u003C\u002Fstrong>Expanding our open, living library of data commons projects worldwide, offering policymakers, practitioners, and funders a resource to learn from proven models.\u003C\u002Fp>\n\u003C\u002Fli>\n\u003Cli dir=\"ltr\" aria-level=\"1\">\n\u003Cp dir=\"ltr\" role=\"presentation\">\u003Cstrong>Blueprint for Developing a Data Commons:\u003C\u002Fstrong> Operationalizing practical guidance on how to design, govern, and sustain data commons in ways that align with community expectations and serve the public interest.\u003Cbr>\u003Cbr>\u003C\u002Fp>\n\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Cp dir=\"ltr\">Together, these efforts will ensure that the Challenge goes beyond awards — laying the foundation for a global movement of data commons that unlock responsible AI for societal good.\u003C\u002Fp>\n\u003Cp dir=\"ltr\">For more information about the New Commons Challenge and the 2025 awardees, visit \u003Ca href=\"http:\u002F\u002Fnewcommons.ai\">newcommons.ai\u003C\u002Fa> or email us at \u003Ca href=\"mailto:newcommons@opendatapolicylab.org\">newcommons@opendatapolicylab.org\u003C\u002Fa>. \u003C\u002Fp>",{},"building-the-future-of-public-interest-ai-certi-amazonia-institute-and-nyu-peace-research-announced-as-winners-of-the-new-commons-challenge","blogposts\u002Fbuilding-the-future-of-public-interest-ai-certi-amazonia-institute-and-nyu-peace-research-announced-as-winners-of-the-new-commons-challenge","1xcmUJxQsFaTHZ0WTtEBOSu0ONfsH8mea2cU5gKyeSo",{"id":83,"brow":84,"cover_image":85,"date":86,"excerpt":9,"extension":10,"heading":87,"main_content":88,"meta":89,"slug":90,"stem":91,"tagline":92,"__hash__":93},"blogposts\u002Fblogposts\u002Fsignals-of-demand-what-the-new-commons-challenge-tells-us-about-the-need-and-opportunity-of-data-commons.json","Phase 1","https:\u002F\u002Fcms.thegovlab.com\u002Fassets\u002Fb6d6aaa1-ef2c-499b-b2db-fc9b7dd0f139","2025-06-12","Signals of Demand: What the New Commons Challenge Tells Us About the Need and Opportunity of Data Commons","\u003Cp dir=\"ltr\">Last week, we closed applications for our \u003Ca href=\"https:\u002F\u002Fblog.thegovlab.org\u002Fthe-new-commons-challenge-advancing-ai-for-public-good-through-data-commons\">New Commons Challenge\u003C\u002Fa>—an open innovation challenge seeking to foster the use of data commons for the development of AI for local decision-making and humanitarian response.\u003C\u002Fp>\n\u003Cp dir=\"ltr\">The response to the New Commons Challenge has been a powerful signal of the growing interest in data commons as a catalyst for public interest AI and locally grounded impact. Between April and June, we received \u003Cstrong>173 submissions\u003C\u002Fstrong> from around the world. \u003C\u002Fp>\n\u003Cp dir=\"ltr\">Although the Challenge focused on two priority areas—humanitarian response and local decision-making—the proposals spanned a wide range of data types and use cases.\u003C\u002Fp>\n\u003Cp dir=\"ltr\">As we move into Phase Two, we are leveraging the current review process as a listening exercise—helping us gauge the appetite for and potential of data commons around the world. What kinds of initiatives are resonating most with AI, data and other practitioners? Where is this momentum coming from—and what can it tell us about the emerging future of collaborative data governance?\u003C\u002Fp>\n\u003Cp>\u003Cstrong> \u003C\u002Fstrong>\u003C\u002Fp>\n\u003Ch3 dir=\"ltr\">Geography\u003C\u002Fh3>\n\u003Cp dir=\"ltr\">Of the 173 submissions, 154 are eligible for the current Phase One review. These entries span 51 countries from across the world and reflect the widespread global interest in data commons initiatives. \u003C\u002Fp>\n\u003Cp dir=\"ltr\" style=\"text-align: center;\">\u003Cimg src=\"https:\u002F\u002Fcms.thegovlab.com\u002Fassets\u002Fd5a80a7d-d077-48bd-b7a7-2a38bd39a2af.png?width=512&height=311\" alt=\"Submissions by Region\">\u003Cbr>\u003Cem>A summary of which regions applicants submitted proposals from\u003C\u002Fem>\u003C\u002Fp>\n\u003Cp dir=\"ltr\" style=\"text-align: center;\">\u003Cimg src=\"https:\u002F\u002Fcms.thegovlab.com\u002Fassets\u002Fb1f49dff-37d7-4241-9c50-82a0126445b3.png?width=512&height=375\" alt=\"Submissions Map\">\u003Cbr>\u003Cem>A mapping of the cities that applicants indicated they were submitting proposals from\u003C\u002Fem>\u003C\u002Fp>\n\u003Cp>\u003Cem>\u003Cstrong> \u003C\u002Fstrong>\u003C\u002Fem>\u003C\u002Fp>\n\u003Cp dir=\"ltr\">Award Type\u003C\u002Fp>\n\u003Cp dir=\"ltr\">Submissions fall into two categories: 103 entries (67%) for Award 1, focusing on creating a new data commons, and 51 entries (33%) for Award 2, focusing on enhancing an existing data commons. \u003C\u002Fp>\n\u003Cp dir=\"ltr\">All applicants have to be affiliated with an established organization, and submissions primarily come from non-profits, start-ups, and research organizations (universities or research institutions).\u003C\u002Fp>\n\u003Ch3 dir=\"ltr\">Applicants \u003C\u002Fh3>\n\u003Cp dir=\"ltr\" style=\"text-align: center;\">\u003Cimg src=\"https:\u002F\u002Fcms.thegovlab.com\u002Fassets\u002F0ff4f380-ceb3-4dd4-a9f4-bd1f3d481e59.png?width=512&height=317\" alt=\"Submissions by Entity Type\">\u003Cbr>\u003Cem>A breakdown of the types of entities that submitted proposals\u003C\u002Fem>\u003C\u002Fp>\n\u003Ch3 dir=\"ltr\">Data and Submission Type\u003C\u002Fh3>\n\u003Cp dir=\"ltr\">Nearly all submissions involve multiple types of data, but the most common dataset types included:\u003C\u002Fp>\n\u003Cul>\n\u003Cli dir=\"ltr\" aria-level=\"1\">\n\u003Cp dir=\"ltr\" role=\"presentation\">Text or unstructured data (language and linguistics, legal data, research and education, news and media, biomedical data)\u003C\u002Fp>\n\u003C\u002Fli>\n\u003Cli dir=\"ltr\" aria-level=\"1\">\n\u003Cp dir=\"ltr\" role=\"presentation\">Structured data (e.g. national statistics, sensor networks, administrative data)\u003C\u002Fp>\n\u003C\u002Fli>\n\u003Cli dir=\"ltr\" aria-level=\"1\">\n\u003Cp dir=\"ltr\" role=\"presentation\">Imagery (e.g. knowledge graphs, spatial images, artwork, data visualizations, geospatial datasets)\u003C\u002Fp>\n\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Cp dir=\"ltr\">Many submissions also incorporated audio and video data, signaling a clear broadening of the types of data being considered for use in data commons. This trend reflects a growing recognition that multimodal data can offer valuable insights, especially when designing AI systems responsive to local needs and contexts.\u003C\u002Fp>\n\u003Cp dir=\"ltr\">The New Commons Challenge is specifically interested in data commons that support disaster response or local decision-making. Around \u003Cstrong>75 submissions \u003C\u002Fstrong>focused exclusively on supporting local decision making. Of the\u003Cstrong> 69 total submissions\u003C\u002Fstrong> focused on humanitarian response, the vast majority also discussed how their data commons would support local decision making in crisis response or prevention. \u003C\u002Fp>\n\u003Cp>\u003Cstrong> \u003C\u002Fstrong>\u003C\u002Fp>\n\u003Ch3 dir=\"ltr\">Next Steps: Phase Two\u003C\u002Fh3>\n\u003Cp dir=\"ltr\">After we conclude our review of Phase One concept notes, selected applicants will be invited to submit a full proposal outlining their use case and implementation. An \u003Ca href=\"https:\u002F\u002Fnewcommons.ai\u002Fjudges\">interdisciplinary group\u003C\u002Fa> will assess proposals for feasibility, innovation, and impact potential. \u003C\u002Fp>\n\u003Cp dir=\"ltr\">Of the shortlisted applications, two teams will each receive $100,000 in funding, along with mentorship, networking opportunities, and global exposure to support the execution of their data commons.\u003C\u002Fp>\n\u003Cp dir=\"ltr\">Decisions will be finalized in the coming months. To learn more about The New Commons Challenge, you can visit \u003Ca href=\"http:\u002F\u002Fnewcommons.ai\">newcommons.ai\u003C\u002Fa>. \u003C\u002Fp>\n\u003Cp> \u003C\u002Fp>",{},"signals-of-demand-what-the-new-commons-challenge-tells-us-about-the-need-and-opportunity-of-data-commons","blogposts\u002Fsignals-of-demand-what-the-new-commons-challenge-tells-us-about-the-need-and-opportunity-of-data-commons","With over 170 applicants spread across six continents and countless sectors, it’s clear that there is an urgent need for resources to develop data commons.","wc8M3Ze_IHd4ZZGM_pTzNI9uszvf2mevDW89D0mDpas",{"id":95,"brow":96,"cover_image":97,"date":98,"excerpt":9,"extension":10,"heading":99,"main_content":100,"meta":101,"slug":102,"stem":103,"tagline":104,"__hash__":105},"blogposts\u002Fblogposts\u002Fdata-commons-the-missing-infrastructure-for-public-interest-artificial-intelligence.json","Opinion Piece","https:\u002F\u002Fcms.thegovlab.com\u002Fassets\u002Fa4e98f26-c3b5-49f2-9ea3-e5252b3916ae","2025-04-29","Data Commons: The Missing Infrastructure for Public Interest Artificial Intelligence","\u003Cp id=\"ember53\" class=\"ember-view reader-text-block__paragraph\">\u003Cem>Stefaan Verhulst (Co-Founder of The GovLab and The Data Tank, Research Prof. \u003C\u002Fem>\u003Ca class=\"IfLmRNJWDKWJahDEmDaCEOnDSeXHtBgyBFDsa \" tabindex=\"0\" href=\"https:\u002F\u002Fwww.linkedin.com\u002Fschool\u002Fnyutandonschoolofengineering\u002F\" data-test-app-aware-link=\"\">NYU Tandon School of Engineering\u003C\u002Fa>\u003Cem>)\u003C\u002Fem>\u003C\u002Fp>\n\u003Cp id=\"ember54\" class=\"ember-view reader-text-block__paragraph\">\u003Ca id=\"ember55\" class=\"ember-view\" href=\"https:\u002F\u002Fwww.linkedin.com\u002Fin\u002Fburton-davis-b5812a8b\u002F\">Burton Davis\u003C\u002Fa> \u003Cem>(Vice President and Deputy General Counsel, Intellectual Property Group at \u003C\u002Fem>\u003Ca class=\"IfLmRNJWDKWJahDEmDaCEOnDSeXHtBgyBFDsa \" tabindex=\"0\" href=\"https:\u002F\u002Fwww.linkedin.com\u002Fcompany\u002Fmicrosoft\u002F\" data-test-app-aware-link=\"\">Microsoft\u003C\u002Fa> \u003Cem>)\u003C\u002Fem>\u003C\u002Fp>\n\u003Cp id=\"ember56\" class=\"ember-view reader-text-block__paragraph\">\u003Ca id=\"ember57\" class=\"ember-view\" href=\"https:\u002F\u002Fwww.linkedin.com\u002Fin\u002Faischroeder\u002F\">Andrew Schroeder\u003C\u002Fa> \u003Cem>(Vice President of Research and Analysis for \u003C\u002Fem>\u003Ca class=\"IfLmRNJWDKWJahDEmDaCEOnDSeXHtBgyBFDsa \" tabindex=\"0\" href=\"https:\u002F\u002Fwww.linkedin.com\u002Fcompany\u002Fdirectrelief\u002F\" data-test-app-aware-link=\"\">Direct Relief\u003C\u002Fa> \u003Cem>)\u003C\u002Fem>\u003C\u002Fp>\n\u003Cp id=\"ember58\" class=\"ember-view reader-text-block__paragraph\">Artificial intelligence is \u003Ca class=\"IfLmRNJWDKWJahDEmDaCEOnDSeXHtBgyBFDsa \" tabindex=\"0\" href=\"https:\u002F\u002Fwww.ecb.europa.eu\u002Fpress\u002Fkey\u002Fdate\u002F2025\u002Fhtml\u002Fecb.sp250401_1~d6c9d8df11.en.html\" target=\"_self\" data-test-app-aware-link=\"\">celebrated\u003C\u002Fa> as the defining technology of our time. From ChatGPT to Copilot and beyond, generative AI systems are reshaping how we work, learn, and govern. But behind the headline-grabbing breakthroughs lies a fundamental problem: The data these systems depend on to produce useful results that serve the public interest is increasingly out of reach.\u003C\u002Fp>\n\u003Cp id=\"ember59\" class=\"ember-view reader-text-block__paragraph\">Without access to diverse, high-quality datasets, AI models risk reinforcing bias, deepening inequality, and returning less accurate, more imprecise results. Yet, access to data remains fragmented, siloed, and increasingly enclosed. What was once open—\u003Ca class=\"IfLmRNJWDKWJahDEmDaCEOnDSeXHtBgyBFDsa \" tabindex=\"0\" href=\"https:\u002F\u002Fwww.brookings.edu\u002Farticles\u002Fthe-us-government-data-purge-is-a-loss-for-policymaking-and-research\u002F\" target=\"_self\" data-test-app-aware-link=\"\">government records\u003C\u002Fa>, \u003Ca class=\"IfLmRNJWDKWJahDEmDaCEOnDSeXHtBgyBFDsa \" tabindex=\"0\" href=\"https:\u002F\u002Fwww.scientificamerican.com\u002Fblog\u002Fobservations\u002Fscientific-research-shouldnt-sit-behind-a-paywall\u002F\" target=\"_self\" data-test-app-aware-link=\"\">scientific research\u003C\u002Fa>, \u003Ca class=\"IfLmRNJWDKWJahDEmDaCEOnDSeXHtBgyBFDsa \" tabindex=\"0\" href=\"https:\u002F\u002Ftheconversation.com\u002Fmeta-just-closed-a-vital-online-research-tool-its-bad-news-for-the-fight-against-misinformation-236785\" target=\"_self\" data-test-app-aware-link=\"\">public media\u003C\u002Fa>—is now locked away by proprietary terms, outdated policies, or simple neglect. We are entering a \u003Ca class=\"IfLmRNJWDKWJahDEmDaCEOnDSeXHtBgyBFDsa \" tabindex=\"0\" href=\"https:\u002F\u002Fpolicylabs.frontiersin.org\u002Fcontent\u002Fcommentary-are-we-entering-a-data-winter\" target=\"_self\" data-test-app-aware-link=\"\">data winter\u003C\u002Fa> just as AI's influence over public life is heating up.\u003C\u002Fp>\n\u003Cp id=\"ember60\" class=\"ember-view reader-text-block__paragraph\">This isn’t just a technical glitch. It’s a structural failure. What we urgently need is new infrastructure: \u003Cstrong>data commons\u003C\u002Fstrong>.\u003C\u002Fp>\n\u003Cp id=\"ember61\" class=\"ember-view reader-text-block__paragraph\">A data commons is a shared pool of data resources—responsibly governed, managed using participatory approaches, and made available for reuse in the public interest. Done correctly, commons can ensure that communities and other networks \u003Ca class=\"IfLmRNJWDKWJahDEmDaCEOnDSeXHtBgyBFDsa \" tabindex=\"0\" href=\"https:\u002F\u002Fincubator.opendatapolicylab.org\u002Ffiles\u002Fdata-commons-for-ai-blueprint.pdf\" target=\"_self\" data-test-app-aware-link=\"\">have a say\u003C\u002Fa> in how their data is used, that public interest organizations can access the data they need, and that the benefits of AI can be applied to meet societal challenges.\u003C\u002Fp>\n\u003Cp id=\"ember62\" class=\"ember-view reader-text-block__paragraph\">Commons offer a practical response to the paradox of data scarcity amid abundance. By pooling datasets across organizations—governments, universities, libraries, and more—they match data supply with real-world demand, making it easier to build AI that responds to public needs.\u003C\u002Fp>\n\u003Cp id=\"ember63\" class=\"ember-view reader-text-block__paragraph\">We’re already seeing early signs of what this future might look like. Projects like \u003Ca class=\"IfLmRNJWDKWJahDEmDaCEOnDSeXHtBgyBFDsa \" tabindex=\"0\" href=\"https:\u002F\u002Fhuggingface.co\u002Fblog\u002FPclanglais\u002Fcommon-corpus\" target=\"_self\" data-test-app-aware-link=\"\">\u003Cstrong>Common Corpus\u003C\u002Fstrong>\u003C\u002Fa>, \u003Ca class=\"IfLmRNJWDKWJahDEmDaCEOnDSeXHtBgyBFDsa \" tabindex=\"0\" href=\"https:\u002F\u002Fmlcommons.org\u002F\" target=\"_self\" data-test-app-aware-link=\"\">\u003Cstrong>MLCommons\u003C\u002Fstrong>\u003C\u002Fa>, and Harvard’s \u003Ca class=\"IfLmRNJWDKWJahDEmDaCEOnDSeXHtBgyBFDsa \" tabindex=\"0\" href=\"https:\u002F\u002Finstitutionaldatainitiative.org\u002F\" target=\"_self\" data-test-app-aware-link=\"\">\u003Cstrong>Institutional Data Initiative\u003C\u002Fstrong>\u003C\u002Fa> show how diverse institutions can collaborate to make data both accessible and accountable. These initiatives emphasize open standards, participatory governance, and responsible reuse. They challenge the idea that data must be either locked up or left unprotected, offering a third way rooted in shared value and public purpose.\u003C\u002Fp>\n\u003Cp id=\"ember64\" class=\"ember-view reader-text-block__paragraph\">But the pace of progress isn’t matching the urgency of the moment. While policymakers debate AI regulation, they often ignore the infrastructure that makes public interest applications possible in the first place. Without better access to high-quality, responsibly governed data, AI for the common good will remain more aspiration than reality.\u003C\u002Fp>\n\u003Cp id=\"ember65\" class=\"ember-view reader-text-block__paragraph\">That’s why we’re launching \u003Ca class=\"IfLmRNJWDKWJahDEmDaCEOnDSeXHtBgyBFDsa \" tabindex=\"0\" href=\"https:\u002F\u002Fnewcommons.ai\u002F\" target=\"_self\" data-test-app-aware-link=\"\">\u003Cstrong>The New Commons Challenge\u003C\u002Fstrong>\u003C\u002Fa>—a call to action for universities, libraries, civil society, and technologists to build data ecosystems that fuel public-interest AI. The initiative will fund two winning projects with $100,000 each to prototype commons focused on critical areas like disaster response and local decision-making. It has secured critical support from leaders in these fields, with \u003Ca class=\"IfLmRNJWDKWJahDEmDaCEOnDSeXHtBgyBFDsa \" tabindex=\"0\" href=\"https:\u002F\u002Fwww.directrelief.org\u002F\" target=\"_self\" data-test-app-aware-link=\"\">Direct Relief\u003C\u002Fa>\u002F\u003Ca class=\"IfLmRNJWDKWJahDEmDaCEOnDSeXHtBgyBFDsa \" tabindex=\"0\" href=\"https:\u002F\u002Fwww.crisisready.io\u002F\" target=\"_self\" data-test-app-aware-link=\"\">CrisisReady\u003C\u002Fa> and the \u003Ca class=\"IfLmRNJWDKWJahDEmDaCEOnDSeXHtBgyBFDsa \" tabindex=\"0\" href=\"https:\u002F\u002Finstitutionaldatainitiative.org\u002F\" target=\"_self\" data-test-app-aware-link=\"\">Institutional Data Initiative\u003C\u002Fa> at the Harvard Law School Library serving as partners and \u003Ca class=\"IfLmRNJWDKWJahDEmDaCEOnDSeXHtBgyBFDsa \" tabindex=\"0\" href=\"https:\u002F\u002Fwww.unesco.org\u002Fen\" target=\"_self\" data-test-app-aware-link=\"\">UNESCO\u003C\u002Fa> serving as an observer.\u003C\u002Fp>\n\u003Cp id=\"ember66\" class=\"ember-view reader-text-block__paragraph\">The New Commons Challenge aims to put this structural and community-guided approach at the forefront. Imagine AI tools that can help cities plan for floods, improve response to crisis, or enable contextual guidance to public interest organizations —not just in well off capitals but in underserved regions around the world. These applications are possible—but only if the right data is available to train and sustain them.\u003C\u002Fp>\n\u003Cp id=\"ember67\" class=\"ember-view reader-text-block__paragraph\">That’s why data commons, and The New Commons Challenge, are so essential.\u003C\u002Fp>\n\u003Cp id=\"ember68\" class=\"ember-view reader-text-block__paragraph\">If we want AI that works in the public’s interest, we need to invest in the infrastructure that makes it possible. A data commons is not a utopian idea. It’s a practical foundation for innovation that reflects—and serves—the diversity of human experience. The commons won’t build itself. But together, we can build it in time.\u003C\u002Fp>",{},"data-commons-the-missing-infrastructure-for-public-interest-artificial-intelligence","blogposts\u002Fdata-commons-the-missing-infrastructure-for-public-interest-artificial-intelligence","The data winter ins't just a technical glitch. It's a structural failure. What we urgently need is new infrastructure: data commons.","vttpSwjk3mAN1cMNArUPxM2qTarZz-2FBn-4OogbsIw",{"id":107,"brow":73,"cover_image":108,"date":109,"excerpt":9,"extension":10,"heading":110,"main_content":111,"meta":112,"slug":113,"stem":114,"tagline":115,"__hash__":116},"blogposts\u002Fblogposts\u002Fthe-new-commons-challenge-advancing-ai-for-public-good-through-data-commons.json","https:\u002F\u002Fcms.thegovlab.com\u002Fassets\u002Fb5e1edcd-a5b9-4e43-a332-9d6703a724bb","2025-04-14","The New Commons Challenge: Advancing AI for Public Good through Data Commons","\u003Cp>\u003Cstrong id=\"docs-internal-guid-cfd79097-7fff-cb4f-2c82-1906a0ff7c5c\">FOR IMMEDIATE RELEASE\u003C\u002Fstrong>\u003C\u002Fp>\n\u003Cp dir=\"ltr\">\u003Cstrong>$200,000 in funding available for innovative data commons that enhance local decision-making and disaster response\u003C\u002Fstrong>\u003C\u002Fp>\n\u003Cp dir=\"ltr\">\u003Cstrong>NEW YORK CITY, New York\u003C\u002Fstrong>—The Open Data Policy Lab, a collaboration between The GovLab at New York University and Microsoft, has launched the \u003Cstrong>New Commons Challenge\u003C\u002Fstrong>, an initiative to advance the responsible reuse of data for AI-driven solutions that enhance local decision-making and humanitarian response. \u003C\u002Fp>\n\u003Cp dir=\"ltr\">The Challenge will award two winning institutions \u003Cstrong>$100,000 each \u003C\u002Fstrong>to develop data commons that fuel responsible AI innovation in these critical areas.\u003C\u002Fp>\n\u003Cp dir=\"ltr\">With the increasing use of generative AI in crisis management, disaster preparedness, and local decision-making, access to diverse and high-quality data has never been more essential. \u003C\u002Fp>\n\u003Cp dir=\"ltr\">The New Commons Challenge seeks to support organizations—including start-ups, non-profits, NGOs, universities, libraries, and AI developers—to build shared data ecosystems that improve real-world outcomes, from public health to emergency response.\u003C\u002Fp>\n\u003Cp dir=\"ltr\">\u003Cstrong>Bridging Research and Real-World Impact\u003C\u002Fstrong>\u003C\u002Fp>\n\u003Cp dir=\"ltr\">“The New Commons Challenge is about putting data into action,” said Stefaan Verhulst, Co-Founder and Chief Research and Development Officer at The GovLab. “By enabling new models of data stewardship, we aim to support AI applications that save lives, strengthen communities, and enhance local decision-making where it matters most.”\u003C\u002Fp>\n\u003Cp dir=\"ltr\">The Challenge builds on the Open Data Policy Lab’s recent report, “\u003Cstrong>Blueprint to Unlock New Data Commons for AI\u003C\u002Fstrong>,” which advocates for creating collaboratively governed data ecosystems that support responsible AI development.\u003C\u002Fp>\n\u003Cp dir=\"ltr\">\u003Cstrong>How the Challenge Works\u003C\u002Fstrong>\u003C\u002Fp>\n\u003Cp dir=\"ltr\">The challenge unfolds in two phases: \u003Cstrong>Phase One: Open Call for Concept Notes (April 14 – June 2, 2025) \u003C\u002Fstrong>\u003C\u002Fp>\n\u003Cp dir=\"ltr\">Innovators world-wide are invited to submit concept notes outlining their ideas. \u003Cstrong>Phase Two: Full Proposal Submissions & Expert Review (June 2025)\u003C\u002Fstrong>\u003C\u002Fp>\n\u003Cul>\n\u003Cli dir=\"ltr\" aria-level=\"1\">\n\u003Cp dir=\"ltr\" role=\"presentation\">Selected applicants will be invited to submit a full proposal\u003C\u002Fp>\n\u003C\u002Fli>\n\u003Cli dir=\"ltr\" aria-level=\"1\">\n\u003Cp dir=\"ltr\" role=\"presentation\">An interdisciplinary panel will evaluate proposals based on their impact potential, feasibility, and ethical governance.\u003C\u002Fp>\n\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Cp dir=\"ltr\">\u003Cstrong>Winners Announced in Late Summer 2025\u003C\u002Fstrong>\u003C\u002Fp>\n\u003Cp dir=\"ltr\">Two selected projects will each receive $100,000 in funding, alongside technical support, mentorship, and global recognition.\u003C\u002Fp>\n\u003Cp dir=\"ltr\">“Generative AI can only be as powerful as the data that informs it. Microsoft is committed to advancing equitable access to public data that enables well-performing and representative AI solutions worldwide,” said Burton Davis, Vice President and Deputy General Counsel at Microsoft.\u003C\u002Fp>\n\u003Cp dir=\"ltr\">\u003Cstrong>A Growing Coalition of Support\u003C\u002Fstrong>\u003C\u002Fp>\n\u003Cp dir=\"ltr\">The Challenge is backed by leading institutions committed to ethical AI and open data. Partners include \u003Cstrong>Direct Relief \u002F CrisisReady,\u003C\u002Fstrong> and \u003Cstrong>Harvard Law School Library\u003C\u002Fstrong>, and \u003Cstrong>UNESCO \u003C\u002Fstrong>as international observer, which will provide subject-matter expertise and evaluation support.\u003C\u002Fp>\n\u003Cp dir=\"ltr\">“We’re seeing a surge in AI-powered tools for disaster response and climate resilience,” said \u003Cstrong>Andrew Schroeder, Vice President of Research and Analysis at Direct Relief and Co-Director of the CrisisReady project with the Harvard Data Science Initiative\u003C\u002Fstrong>. “For these tools to produce genuine public benefit, they require \u003Cstrong>high-quality, diverse datasets\u003C\u002Fstrong>—which is exactly what the New Commons Challenge is driving forward.”\u003C\u002Fp>\n\u003Cp dir=\"ltr\">Harvard Law School Library’s \u003Cstrong>Greg Leppert, Executive Director of the Institutional Data Initiative\u003C\u002Fstrong>, added: “Expanding access to data is key to ensuring that, as the potential of AI grows, all of humanity is empowered along with it. Our work with libraries to publish vast data collections of knowledge is born from the same public-interest principles that animate this Challenge.”\u003C\u002Fp>\n\u003Cp dir=\"ltr\">UNESCO’s \u003Cstrong>Guilherme Canela de Souza Godoi, Director for the Division of Digital Inclusion and Policies and Digital Transformation\u003C\u002Fstrong>, emphasized the broader implications: “As we have been emphasizing in several multilateral recommendations and guidelines, ethical and human rights-based approaches must guide innovation. The New Commons Challenge offers a concrete framework for how data collaboration can align AI with societal needs.”\u003C\u002Fp>\n\u003Ch3 dir=\"ltr\">Join the Challenge\u003C\u002Fh3>\n\u003Cp dir=\"ltr\">The New Commons Challenge is now open for applications. Interested participants can find more details, including the full challenge guidelines, at\u003Cstrong> \u003Ca href=\"http:\u002F\u002Fnewcommons.ai\">newcommons.ai\u003C\u002Fa>.\u003C\u002Fstrong>\u003C\u002Fp>\n\u003Cp dir=\"ltr\">For inquiries, please contact: \u003Cstrong>newcommons@opendatapolicylab.org.\u003C\u002Fstrong>\u003C\u002Fp>",{},"the-new-commons-challenge-advancing-ai-for-public-good-through-data-commons","blogposts\u002Fthe-new-commons-challenge-advancing-ai-for-public-good-through-data-commons","The Open Data Policy Lab—a collaboration between Microsoft and The GovLab—is seeking out interesting ideas on how data commons might be used to support AI for local decision-making and generative AI.","5WmeZsuRds4Ml1g5DVYR2nG-ne_ScLiZgCg0owK0YBs",{"id":118,"brow":119,"cover_image":120,"date":121,"excerpt":9,"extension":10,"heading":122,"main_content":123,"meta":124,"slug":125,"stem":126,"tagline":127,"__hash__":128},"blogposts\u002Fblogposts\u002Flaunch-a-blueprint-to-unlock-new-data-commons-for-artificial-intelligence.json","New Publication","https:\u002F\u002Fcms.thegovlab.com\u002Fassets\u002F9250c6dd-f1ea-420f-9bb0-cce6a4b619e0","2025-03-11","Launch: A Blueprint to Unlock New Data Commons for Artificial Intelligence","\u003Cp dir=\"ltr\">In today’s rapidly evolving AI landscape, it is critical to broaden access to diverse and high-quality data to ensure that AI applications can serve all communities equitably. Yet, we are on the brink of a potential \"\u003Ca href=\"https:\u002F\u002Fsverhulst.medium.com\u002Fare-we-entering-a-data-winter-f654eb8e8663\">data winter\u003C\u002Fa>,\" where valuable data assets that could drive public good are increasingly locked away or inaccessible. \u003C\u002Fp>\n\u003Cp dir=\"ltr\">Data commons—collaboratively governed ecosystems that enable responsible sharing of diverse datasets across sectors—offer a promising solution. By pooling data under clear standards and shared governance, data commons can unlock the potential of AI for public benefit while ensuring that its development reflects the diversity of experiences and needs across society.\u003C\u002Fp>\n\u003Cp dir=\"ltr\">\u003Cimg style=\"display: block; margin-left: auto; margin-right: auto;\" src=\"https:\u002F\u002Fcms.thegovlab.com\u002Fassets\u002F9cd1ddf9-5a67-402d-b648-8707d130cb39?width=499&height=656\" alt=\"Screenshot 2025 03 11 144711\">\u003C\u002Fp>\n\u003Cp dir=\"ltr\">To accelerate the creation of data commons, The Open Data Policy, today, releases “\u003Ca href=\"https:\u002F\u002Fincubator.opendatapolicylab.org\u002Ffiles\u002Fdata-commons-for-ai-blueprint.pdf\">A Blueprint to Unlock New Data Commons for AI\u003C\u002Fa>”—a guide on how to steward data to create data commons that enable public-interest AI use cases. \u003C\u002Fp>\n\u003Cp dir=\"ltr\">Co-authored by Hannah Chafetz, Andrew J. Zahuranec, and Stefaan Verhulst the document is aimed at supporting libraries, universities, research centers, and other data holders (e.g. governments and nonprofits) through four modules:\u003C\u002Fp>\n\u003Cul>\n\u003Cli dir=\"ltr\" aria-level=\"1\">\n\u003Cp dir=\"ltr\" role=\"presentation\">\u003Cstrong>Mapping the Demand and Supply\u003C\u002Fstrong>: Understanding why AI systems need data, what data can be made available to train, adapt, or augment AI, and what a viable data commons prototype might look like that incorporates stakeholder needs and values;\u003C\u002Fp>\n\u003C\u002Fli>\n\u003Cli dir=\"ltr\" aria-level=\"1\">\n\u003Cp dir=\"ltr\" role=\"presentation\">\u003Cstrong>Unlocking Participatory Governance\u003C\u002Fstrong>: Co-designing key aspects of the data commons with key stakeholders and documenting these aspects within a formal agreement;\u003C\u002Fp>\n\u003C\u002Fli>\n\u003Cli dir=\"ltr\" aria-level=\"1\">\n\u003Cp dir=\"ltr\" role=\"presentation\">\u003Cstrong>Building the Commons\u003C\u002Fstrong>: Establishing the data commons from a practical perspective and ensure all stakeholders are incentivized to implement it; and\u003C\u002Fp>\n\u003C\u002Fli>\n\u003Cli dir=\"ltr\" aria-level=\"1\">\n\u003Cp dir=\"ltr\" role=\"presentation\">\u003Cstrong>Assessing and Iterating\u003C\u002Fstrong>: Evaluating how the commons is working and iterating as needed.\u003C\u002Fp>\n\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Cp dir=\"ltr\" style=\"text-align: center;\">\u003Cimg src=\"https:\u002F\u002Fcms.thegovlab.com\u002Fassets\u002F9ba5ed82-8925-4f36-bd94-be90636bbfc4?width=600&height=361\" alt=\"Screenshot 2025 03 11 143319\">\u003C\u002Fp>\n\u003Cp dir=\"ltr\">These modules are further supported by two \u003Ca href=\"https:\u002F\u002Fincubator.opendatapolicylab.org\u002Ffiles\u002Fappendix%20b.pdf\">supplementary taxonomies\u003C\u002Fa>. “The Taxonomy of Data Types” provides a list of data types that can be valuable for public-interest generative AI use cases. The “Taxonomy of Use Cases” outlines public-interest generative AI applications that can be developed using a data commons approach, along with possible outcomes and stakeholders involved. \u003C\u002Fp>\n\u003Cp dir=\"ltr\">A separate set of \u003Ca href=\"https:\u002F\u002Fincubator.opendatapolicylab.org\u002Ffiles\u002Fappendix%20a_fillable.pdf\">worksheets\u003C\u002Fa> can be used to further guide organizations in deploying these tools.\u003C\u002Fp>\n\u003Cp dir=\"ltr\">We hope these resources offer a meaningful starting point for organizations aiming to unlock data that can be leveraged for generative AI for the public good. The blueprint is intended as a living document that will be updated over time to reflect new developments and insights in this rapidly evolving landscape.. \u003C\u002Fp>\n\u003Cp dir=\"ltr\">Please reach out to us at \u003Ca href=\"mailto:datastewards@thegovlab.org\">datastewards@thegovlab.org\u003C\u002Fa> if you use any of these materials or any of our other \u003Ca href=\"https:\u002F\u002Ftools.opendatapolicylab.org\u002F\">tools\u003C\u002Fa> to support your work or have any questions. Want to stay up to date on future releases? Sign up \u003Ca href=\"https:\u002F\u002Fthegovlab.us6.list-manage.com\u002Fsubscribe?u=1a990feb5c&id=bc6d09925f\">HERE\u003C\u002Fa>.\u003C\u002Fp>\n\u003Cp data-block-key=\"ap6d3\"> \u003C\u002Fp>",{},"launch-a-blueprint-to-unlock-new-data-commons-for-artificial-intelligence","blogposts\u002Flaunch-a-blueprint-to-unlock-new-data-commons-for-artificial-intelligence","To accelerate the creation of data commons, The Open Data Policy, today, releases “A Blueprint to Unlock New Data Commons for AI”—a guide on how to steward data to create data commons that enable public-interest AI use cases. ","17rxYn7qYTnFEbXVwpsgOi0kxvF0lXkXJ7pSK3yY1Eg",1784574602724]